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Predictive maintenance in the IIoT

rscasny — Sat, 08 Oct 2022 21:20:09 GMT

Current Revision posted to Documents by rscasny on 10/8/2022 9:20:09 PM

The Industrial Internet of Things (IIoT) has allowed for increased productivity and operational efficiency across manufacturing and industrial sectors, but until now maintenance has often been overlooked.

According to a 2014 report from market researcher Frost & Sullivan, the IIoT and big data analytics will enable industrial maintenance to shift from corrective to more preventative and predictive in the next five years. Preventative and predictive industrial maintenance can lead to optimized costs and a decrease in unplanned downtime.

Below are just a few ways the IIoT is making this possible.

Risk analysis

Using predictive analytics, industrial maintenance workers can assess potential equipment vulnerabilities, and model the lifetime and potential reliability of equipment. To support this advanced technology, the skillset of the maintenance worker has to be adjusted and workers need to be trained to use an IIoT-based platform. IT and communication infrastructures also need to be overhauled or improved prior to using predictive IIoT models. Once the maintenance staff is trained and new technology is implemented, the risk analysis can be easily completed on user-friendly data management platforms.

Failure detection

The last thing any maintenance worker wants is an equipment failure, as it can either immensely slow down or completely halt the manufacturing process altogether. IIoT and predictive analytics provide accurate predictions of equipment or component failure, reduce unplanned equipment downtime and enable preventative service and maintenance. Rather than waiting for equipment to fail, dynamic maintenance schedules can be built based on real-time data from IIoT sensors. With these processes in place, it also opens the door for increased scalability without concerns surrounding equipment failures as a result of growth.

Compliance

The IIoT also enables maintenance workers to increasingly meet business and regulatory compliance standards. As manufacturing processes increasingly move online, IIoT-based platforms promote a shift toward encryption methods and also include features for automatic compliance identification. From aviation, to electronic components and every manufacturing industry in between, there are countless compliance requirements maintenance staff must keep in mind. Predictive analytics ensure all equipment and systems stay as up-to-date as possible on all compliance policies.

Not only do preventative and predictive industrial maintenance lead to decreased downtime and an uptick in efficiency, but other key benefits include long-term planning of product and equipment updates or refurbishments, easier visibility and monitoring, and the ability to detect any potential problems at the earliest stage possible.

Tags: predictive maintenance, iiot, internet of things, industrial maintenance

Beyond the PLC: A Primer on Automation Panels

rscasny — Wed, 06 Oct 2021 20:54:16 GMT

Current Revision posted to Documents by rscasny on 10/6/2021 8:54:16 PM

In the early days of automation, original equipment manufacturers (OEMs) shipped control systems with rack-mounted PLC’s, pilot lights, gauges, and push buttons. Over the years, the vast majority have simplified their systems by migrating to operator interface (OI) panels in place of other panel mount components. To reduce wiring costs and to make it easier to ship their equipment in modular sections, many have also moved to distributed IO.

And, in an effort to further reduce the cost associated with reactive maintenance, many OEMs are now adding secure remote connectivity to access end user networks to perform remote program modifications and analyze equipment performance. Typically, an OEM machine would utilize an automation panel consisting of a programmable automation controller (PAC) with distributed IO, a touchscreen operator interface with data logging, and an industrial security router. The PAC, OI, and router each have their own processor, their own installation requirements, and their own unique software configuration. Automation panels combine the programmable controller functionality and the operator interface into a single unit.

Backgrounder

Automation panels entered the market about 15 years ago. Many of these early units were simply operator interface panels with some local IO, ladder logic, and a flat database. Modern automation panels like the GE QuickPanel+ include the full IEC61131 programming languages (Ladder, Structured Text, Function Block Diagram, Sequential Function Chart, and Instruction List), as well as user-defined data structures and user-defined function blocks.

It may be more accurate to describe these automation panels as PAC controllers with a built-in operator interface, rather than just an operator interface that performs control. In the case of the QuickPanel+, OEMs can purchase a remote security software package from Secomea™ that will allow the OEM to securely connect to the QuickPanel+ over the Internet using the customer’s existing network, eliminating the need for a separate security router. The advantages of this simplified architecture include cost savings, simplified maintenance, and improved performance.

Benefits

Automation panels can significantly reduce software development costs. Many automation suppliers tout the benefits of a shared database between the PAC and the OI panel, but if these are separate devices, then they still have separate databases at run time. This means that each time you add a variable, you need to download to both devices. If the controller and OI get out of sync, you end up with communication errors and possibly unexpected operation. Automation panels truly use a single database with a single development environment and a single library for reusable objects. Hardware costs are also reduced. Combining the controller, operator interface, and remote connectivity into a single device means only one device to purchase, install, and configure. This saves money on both production time and on panel space.

Maintaining one device is less work than maintaining three, especially when you have shipped a system to an end user that may be hundreds or thousands of miles away. With an automation panel, you can back up the operator interface and logic program on a single memory card or USB stick. If the end user has separate files for the operator interface and controller and needs to restore one or both programs, they might load different revisions and end up with a non-working system. Having a single program to restore is easier and eliminates version compatibility issues. A single device means a single point of connect. There is no need to connect to multiple ports to monitor or upgrade the system.

Performance

It may sound counter-intuitive, but combining the PLC and OI into a single device can actually improve the update times for the operator interface in many applications. This is because one of the main CPU tasks for a traditional operator interface is communications with the controller. When today’s operators press a button on the OI screen, they expect an immediate response for the equipment and immediate feedback on the graphic screen. The biggest reason for delays in that response is the communication driver between the OI panel and the PLC. With an automation panel, this communication is much faster, because it is internal to the device. There is no need to rely on serial or Ethernet communication links for updating operator screens.

Automation panels offer the same deterministic real-time control as traditional programmable controllers. Programmable controllers are a better fit for extremely fast scan times, very large IO counts, or high performance redundancy. For low- to mid-range applications that require a dedicated operator interface, automation panels like the QuickPanel+ provide a simplified architecture with easy remote connectivity options and lower total cost of ownership.

To learn more about Automation Panels, please download the attached document by GE Intelligent Platforms called "Automation Panels vs PLC in System Control," which was the source of information for this document.

Attachments:

community.element14.com/.../automation_2D00_panels_2D00_vs_2D00_plc_2D00_in_2D00_system_2D00_control_2D00_wp_2D00_gft886.pdf

automation-panels-vs-plc-in-system-control-wp-gft886.pdf

Tags: plc, automation panels, programmable automation controller

The Difference Between a Soft Starter and a Variable Frequency Drive

rscasny — Wed, 06 Oct 2021 20:54:12 GMT

Current Revision posted to Documents by rscasny on 10/6/2021 8:54:12 PM

Motors often require large amounts of energy when quickly accelerating to full speed. Soft starters and variable frequency drives can both be used to reduce inrush currents and limit torque--protecting equipment and extending the life of a motor by reducing motor heating caused by frequent starts and stops. But there are a number of differences between a soft starter and a variable frequency drive.

Soft Starters

A soft starter is a solid-state device that protects AC electric motors from damage caused by sudden influxes of power by limiting the large initial inrush of current associated with motor startup. They provide a gentle ramp up to full speed and are used only at startup (and stop, if equipped). Ramping up the initial voltage to the motor produces this gradual start. Soft starters are also known as reduced voltage soft starters (RVSS).

Soft starters are used in applications that require speed and torque control are required only during startup (and stop if equipped with soft stop) or where there is a need to reduce large startup inrush currents associated with a large motor is required. They are also used when the mechanical system (the load) requires a gentle start to relieve torque spikes and tension associated with normal startup (for example, conveyors, belt-driven systems, gears, and so on). And they are used for pumps to eliminate pressure surges caused in piping systems when fluid changes direction rapidly.

Electrical soft starters temporarily reduce voltage or current input by reducing torque. Some soft starters may use solid-state devices to help control the flow of the current. They can control one to three phases, with three-phase control usually producing better results. Most soft starters use a series of thyristors or silicon controlled rectifiers (SCRs) to reduce the voltage. In the normal OFF state, the SCRs restrict current, but in the normal ON state, the SCRs allow current. The SCRs are engaged during ramp up, and bypass contactors are pulled in after maximum speed is achieved. This helps to significantly reduce motor heating. Soft starters are often the more economical choice for applications that require speed and torque control only during motor startup. Additionally, they are often the ideal solution for applications where space is a concern, as they usually take up less space than variable frequency drives.

Variable Frequency Drives

A variable frequency drive (VFD) is a motor control device that protects and controls the speed of an AC induction motor. A VFD can control the speed of the motor during the start and stop cycle, as well as throughout the run cycle. VFDs are also referred to as adjustable frequency drives (AFDs). VFDs are used in applications where omplete speed control is required, energy savings is a goal and custom control is needed.

VFDs convert input power to adjustable frequency and voltage source for controlling speed of AC induction motors. The frequency of the power applied to an AC motor determines the motor speed.

The VFD's input power comes from the facility power network (typically 480V, 60 Hz AC). It has a rectifier that converts network AC power to DC power. A filter and DC bus work together to smooth the rectified DC power and to provide clean, low ripple DC power to the inverter, which uses DC power from the DC bus and filter to invert an output that resembles sine wave AC power using a pulse width modulation (PWM) technique.

VFD's can save a lot of energy. And they are good at reducing peak energy demand or reducing power when not required. They offer fully adjustable speed (pumps, conveyors, and fans) and can control starting, stopping, and acceleration. they have dynamic torque control and they provide smooth motion for applications such as elevators and escalators. They can maintain speed of equipment, making them ideal for manufacturing equipment and industrial equipment such as mixers, grinders, and crushers. They have self-diagnostics and communications, advanced overload protection, PLC-like functionality and software programming, digital inputs/outputs (DI/DO), analog inputs/outputs (AI/AO) and relay outputs.

To learn more about soft starters and variable frequency drives, please download the attached document by Eaton, called "Choosing between a soft starter and a variable frequency drive," which was the source of information for this document.

Attachments:

community.element14.com/.../Choosing-between-a-soft-starter-and-a-variable-frequency-drive.pdf

Choosing between a soft starter and a variable frequency drive.pdf

Tags: soft starters, cuttler hammer, ac motors, eaton, ac drives, variable frequency drives

Industrial Big Data's Time Has Come

rscasny — Wed, 06 Oct 2021 20:54:10 GMT

Current Revision posted to Documents by rscasny on 10/6/2021 8:54:10 PM

Massive amounts of operational data are coming online with the ever-increasing set of advanced devices and equipment, as a result of a movement often referred to as the Industrial Internet. Big data is the proliferation of data from these systems, devices and applications whose size makes it challenging to capture, manage, and process within a tolerable period of time using traditional software solutions.

Businesses everywhere, including industrial enterprises, face mounting pressure to stay competitive with data-driven strategies—requiring increasingly more data, which results in the accumulation of larger and larger data sets. In addition, evolving and evermore stringent regulatory requirements necessitate the collection of more information as proof for audit and compliance purposes.

Beyond the Capability of Traditional Data Management Systems

The volume of data (ranging from a few dozen terabytes to many petabytes of data in a single data set) from which to extract value is beyond the capability of a traditional data management system. What is more, the challenge of managing big data for industry goes beyond the sheer volume of information; there is the diversity and complexity of data, which comes in various formats and from disparate sources. There are typically “islands” of process information that must be aggregated, stored, and analyzed to derive context and meaningful value.

To leverage big data, industrial businesses need the ability to support different types of information, the infrastructure to store massive data sets, and the flexibility to leverage the information once it is collected and stored—enabling historical analysis of critical trends to enable real-time predictive analysis. As businesses increasingly realize that much more of their value proposition is information-based, technologies that can address big data are quickly gaining traction.

Luckily for industrial companies, Google, Yahoo and Facebook are pushing the envelope on big data needs. Their desire to analyze clickstreams, web logs, and social interactions has forced them to create new tools for storing and analyzing large data sets.One of those tools is Hadoop.

Hadoop for Industrial Data Sets

Hadoop is an Open Source technology that is rapidly evolving. It is a tool that enables data storage scale through the use of commodity hardware, distributing data across many low-cost computers. Once distributed, new challenges arise in locating and processing the data, which are addressed by MapReduce, a framework where data is processed in parallel across many nodes in a cluster. It allows processing to be mapped to the data across many locations, and then reduces the outputs for similar data elements into a single result.

While Hadoop may have big promise for handling large data sets, the complexity involved and the specialized skillset needed to create a Hadoop environment is often beyond the ability of industrial businesses. Yet these businesses still need to scale across the enterprise to handle large sets of time-series data generated in manufacturing and other industrial operations.

For example, a manufacturing manager may want to understand the significance of temperature variation on quality as the rate of flow of materials varies through a production line; or a power plant supervisor may want to analyze five years of past data to examine anomalies and variations to understand whether they were followed by subsequent outages to enable predictive analysis. This level of operational insight requires the ability to quickly run a query against large data sets for specific time periods—a unique and powerful capability that calls for an industrial data solution.

Historian Software

As data sets grow larger and more complex, advanced historian software offer an effective, simple, and easy way for companies to efficiently leverage vast amounts of real-time and historical process data, a critical need for optimized decision support. They help companies easily connect and collect their data from various systems and devices, making it accessible to uncover intelligence that would otherwise be locked away in the data.

While historian software may not yet be top of mind when it comes to industrial big data solutions, what many companies may not realize is that these advanced, out-of-the-box solutions are specifically designed to efficiently collect, store and manage large volumes of time-series process data, which is precisely the industrial big data challenge.

To learn more about industrial big data, Hadoop and Advanced Historian Software, please download the attached document below called, GE Intelligent Platforms’ The Rise of Industrial Big Data, which was the source of information for this document.

Attachments:

community.element14.com/.../the_5F00_rise_5F00_of_5F00_industrial_5F00_big_5F00_data.pdf

the_rise_of_industrial_big_data.pdf

Tags: hadoop, industrial internet, industrial big data, eejournal, historian software

Industrial Ethernet Protocols Simplified: EtherCAT, EtherNet/IP, PROFINET, Sercos III, Modbus /TCP

rscasny — Wed, 06 Oct 2021 20:54:01 GMT

Current Revision posted to Documents by rscasny on 10/6/2021 8:54:01 PM

The increasingly connected world is inevitably connecting the factory floors. Human machine interfaces (HMIs), programmable logic controllers (PLCs), motor control and sensors need to be connected in a scalable and efficient way. The industrial Ethernet has gained popularity, becoming more ubiquitous and offering higher speed, increased connection distance, and the ability to connect more nodes. There are many different industrial Ethernet protocols driven by various industrial equipment manufacturers. These protocols include EtherCAT®, PROFINET®, EtherNet/IP™, Sercos® III and CC-Link®, among others. Let's take a quick tour of these protocols.

Industrial Automation Systems

There are four major components in industrial automation including PLC controllers, HMI panels, industrial drives and sensors. The PLC controller is the brain of an industrial automation system; it provides relay control, motion control, industrial input and output process control, distributed system, and networking control. The HMI is the graphical user interface for industrial control. It provides a command input and feedback output interface for controlling the industrial machinery. An HMI is connected through common communication links to other parts of industrial systems. Industrial drives are motor controllers used for controlling optimal motor operation. Sensors are the hands and legs of the industrial automation system that monitor the industrial operation conditions, inspections, measurements, and more, in real time. Communication is the backbone of all the industrial components for efficient automation production systems.

Industrial Ethernet Communication Protocols

Ethernet is becoming ubiquitous and cost effective, with common physical links and increased speed. As such, many industrial communication protocols are moving to Ethernet-based solutions. Ethernet communications with TCP/IP typically are non-deterministic, and reaction time is often around 100 ms. Industrial Ethernet protocols use a modified Media Access Control (MAC) layer to achieve very low latency and deterministic responses. Ethernet also enables a flexible network topology and a flexible number of nodes in the system. Let’s look at some of the popular Industrial Ethernet protocols in detail.

EtherCAT was originally developed by Beckhoff to enable on-the-fly packet processing and deliver real-time Ethernet to automation applications and that can provide scalable connectivity for entire automation systems, from large PLCs all the way down to the I/O and sensor level. EtherCAT, a protocol optimized for process data, uses standard IEEE 802.3 Ethernet Frames. Each slave node processes its datagram and inserts the new data into the frame while each frame is passing through. The process is handled in hardware so each node introduces minimum processing latency, enabling the fastest possible response time. EtherCAT is the MAC layer protocol and is transparent to any higher level Ethernet protocols such as TCP/IP, UDP, Web server, etc. EtherCAT can connect up to 65,535 nodes in a system, and EtherCAT master can be a standard Ethernet controller, thus simplifying the network configuration. Due to the low latency of each slave node, EtherCAT delivers flexible, low-cost and network-compatible industrial Ethernet solutions.

EtherNet/IP is an industrial Ethernet protocol originally developed by Rockwell. Unlike EtherCAT, which is MAC-layer protocol, EtherNet/IP is application-layer protocol on top of TCP/IP. EtherNet/IP uses standard Ethernet physical, data link, network and transport layers, while using Common Industrial Protocol (CIP) over TCP/IP. CIP provides a common set of messages and services for industrial automation control systems, and it can be used in multiple physical media. For example, CIP over CAN bus is called DeviceNet, CIP over dedicated network is called ControlNet and CIP over Ethernet is called EtherNet/IP. EtherNet/IP establishes communication from one application node to another through CIP connections over a TCP connection, and multiple CIP connections can be established over one TCP connection. EtherNet/IP uses the standard Ethernet and switches, thus it can have an unlimited number of nodes in a system. This enables one network across many different end points in a factory floor. EtherNet/IP offers complete producer-consumer service and enables very efficient slave peer-to-peer communications. EtherNet/IP is compatible with many standard Internet and Ethernet protocols but has limited real-time and deterministic capabilities.

PROFINET is widely used industrial Ethernet by major industrial equipment manufactuerers such as Siemens and GE. It has three different classes. PROFINET Class A provides access to a PROFIBUS network through proxy, bridging Ethernet and PROFIBUS with a remote procedure calling on TCP/IP. Its cycle time is around 100ms, and it is mostly used for parameter data and cyclic I/O. The typical application includes infrastructure and building automation. PROFINET Class B, also referred as PROFINET Real-Time (PROFINET RT), introduces a software-based real-time approach and has reduced the cycle time to around 10ms. Class B is typically used in factory automation and process automation. PROFINET Class C (PROFINET IRT), is Isochronous and Real-Time, requiring special hardware to reduce the cycle time to less than 1ms to deliver the sufficient performance on the real-time industrial Ethernet for motion control operations.

Sercos III is the third generation of Serial Real-time Communication System (Sercos). It combines on-the-fly packet processing for delivering real-time Ethernet and standard TCP/IP communication to deliver low latency industrial Ethernet. Much like EtherCAT, a Sercos III slave processes the packet by extracting and inserting data to the Ethernet frame on-the-fly to achieve low latency. Sercos III separates input and output data into two frames. With cycle times from 31.25 microseconds, it is as fast as EtherCAT and PROFINET IRT. Sercos III supports ring or line topology. One key advantage to using ring topology is communication redundancy. Even if the ring breaks due to failure of one slave, all remaining slaves still get the Sercos III frames with input/output data. Sercos III can have 511 slave nodes in one network and is most used in servo drive controls.

CC-Link IE is the industrial Ethernet technology of CC-Link, which was originally developed by Mitsubishi. CC-Link IE has two versions: CC-Link IE Control and CC-Link IE Field. CC-Link IE control is intended for controller-to-controller communications and can have 120 nodes per network. CC-Link IE field is intended for I/O communications and motion control, and it can have 254 nodes per network. CC-Link IE leverages the Ethernet data link layer, and its control frames are directly embedded in the Ethernet frame. Only ring topology is supported in CC-Link without switches. This can provide network redundancy, but a limited number of nodes can be supported in a network, and the cycle time is dependent on the number of the nodes in the network.

Modbus /TCP, an extension of Modbus, was originally developed by Schneider Electric and uses Modbus messaging over TCP/IP on top of Ethernet. Modbus/TCP is simple to implement on the standard Ethernet network, but it does not guarantee real-time and deterministic communications.

To learn more about Industrial Ethernet Communication Protocols, please download below the pdf by Texas Instruments called, An inside look at industrial Ethernet communication protocols, which was the source of information for this document.

Attachments:

community.element14.com/.../An-inside-look-at-industrial-Ethernet-communication-protocols-by-Texas-Instruments.pdf

An inside look at industrial Ethernet communication protocols by Texas Instruments.pdf

Tags: industrial ethernet communication protocols, profinet, eejournal, ethernet/ip, modbus /tcp, ethercat, sercos iii

The Impending Tide of Industrial Automation

tariq.ahmad — Wed, 06 Oct 2021 20:53:02 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:53:02 PM

More than 50 years ago, automation changed the outlook of manufacturing industries for good. General Motors’ Unimate, the first industrial robot of its kind, sped up the completion of routine tasks and ushered in an era of streamlined production. Advancements in technology, however, have enabled automation to assume a much larger role in industrial maintenance and repair that are changing the traditional role of the engineer.

Emerging technologies

The introduction of automation has enabled manufacturers to cut costs and operate more efficiently than ever before. One such innovation that has helped improve the manufacturing process is Eureqa, machine intelligence software from Nutonian, Inc. that can analyze manufacturing data to improve the performance and reduce the cost of titanium turbine engine components. The software is so effective that it erases the need for actual engineers who use data to forecast the performance of manufactured parts.

Further enhancements in technology have spurred the development of robots at production plants of French car manufacturer Renault, which are much less clumsy than previous assembly line robots. In fact, these robots have the ability to put together small parts and reach even the most difficult spots on a vehicle. They can also operate in close proximity to other workers by using cameras to detect if they are nearby. The robot is then alerted of their presence and directed to slow down or stop completely, putting to rest the notion that such robots are dangerous.

Adapting to change

Despite being decades old, the idea of automation isn’t going away anytime soon. The global market for industrial automation equipment (IAE) continues to grow at steady rates. By 2017, revenues from the IAE market are expected to rise all the way to $225 billion. The expansion of automation places traditional industrial engineers in a precarious position - understand and prepare for these changes or face the possibility of being outpaced by increasingly sophisticated automation technology.

Engineers can and should take advantage of ways in which they can boost their value to manufacturers. In particular, there will be a need for engineers who can analyze and decide how automated technology should best be integrated within existing manufacturing processes and procedures.

In addition, engineers can foster the cycle of constant innovation by identifying potential improvements in automation. While automated software systems might be able to process information more quickly than humans, industrial engineers have the opportunity to expand on the limitations of a coded program.

The rise of state-of-the-art technology will certainly alter the roles and responsibilities of conventional industrial engineers, but they will not become obsolete altogether. Engineers have a reputation for overcoming the toughest challenges. Working alongside automated technology is no exception.

The 2 Biggest Engineering Challenges Posed by the Industrial Internet of Things

tariq.ahmad — Wed, 06 Oct 2021 20:53:02 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:53:02 PM

Visions of a world in which humans and computers are data-linked and machines make autonomous decisions have filled the pages of science fiction books for decades. Thanks to the affordability of semiconductors and the ever-accelerating speeds of the Internet, what was once fantasy is now on the horizon.

The movement toward a future of interconnected objects in our homes, in our offices and in large-scale organized systems has been branded as “The Internet of Things.” And while the idea of self-driving cars and interior lighting that automatically adjusts to your mood will inevitably seize the imagination of the public, it is the Industrial Internet of Things (IIoT) that will likely have the greatest impact on our world.

IIoT will be a large subset of the greater IoT, which Cisco CEO John Chambers predicts to be a $19 trillion market. As it primarily applies to the energy, infrastructure and manufacturing sectors, the IIoT is expected to greatly increase efficiency, adaptability and growth while reducing waste, limiting latency and minimizing risk. There is vast potential for digitizing our energy efforts, multiplying our manufacturing capacities, automating the data grid and making our cities far more intelligent than our phones.

But before the Industrial Internet of Things becomes a reality, there are two big hurdles that engineers must work to overcome.

1. Security & Data Privacy

Cybersecurity has consistently made headlines ever since large scale breaches were reported across some of the biggest U.S. retailers back in 2013. Malevolent hackers are constantly trying to access consumer financial information, and cyberspace has become a battlefield as strategically important as any physical location. Before the civilized world can enjoy the immense benefits of IIoT, engineers must design security systems that can prevent the grids from being compromised. This is no small task, as an interconnected industrial world brings with it a multitude of new entry points for hackers, cyberterrorists and warring nations. New security technology and protocols will need to be implemented for every user touchpoint, as well as every added layer of the IIoT system.

2. Interoperability

With the rise of consumer electronics, engineers had to figure out how to allow each device to perform its function without drowning in electromagnetic interference. The challenge with entire connected systems will be less of a noise issue and more of a compatibility issue. If a variety of different technologies are used to deploy different data grids, it will likely prove very difficult to make those grids communicate with one another. To achieve seamless communication among all systems within the IIoT, engineers within the Industrial Internet Consortium--a partnership of more than 150 companies--are developing unified standards for IIoT communication that they plan to present to the National Institute of Standards and Technology (NIST) by 2018. This effort is necessary and promising, but it is the beginning of a long and arduous process that will test the mettle and ingenuity of our engineers.

If the Industrial Internet of Things is to become reality, these two fundamental issues of security and interoperability will need to be solved first. Both problems will likely be moving targets that will change and grow as we attempt to scale the IIoT across industries and infrastructures. But the value of smart, adaptable systems that thrive on seamless data-sharing is undeniable. When engineers build it, science fiction fans may well say that the future has finally arrived.

Standardizing the smart factory

tariq.ahmad — Wed, 06 Oct 2021 20:53:01 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:53:01 PM

The Internet of Things (IoT) and digital connectivity are leading to what many are calling the “Fourth Industrial Revolution.” The First Industrial Revolution used water and steam to streamline production, the Second used electricity for mass production and the Third used electronics and information technology for production automation. For this Fourth Industrial Revolution and smart factories to be successful, adhering to industry standards can ensure affordable, quick and more reliable manufacturing.

A handful of countries, including China, Japan, South Korea and the U.S., are working together to create global standards for smart factories, but the rest of the world has been, for the most part, inactive on this front. Rather than creating proprietary smart factories and related technology, here are a few examples of standards than can be put in place across the industry.

Communications and sensors

One of the benefits of smart manufacturing is machines’ capabilities to communicate with one another, increasing efficiency. OPC Unified Architecture (OPC UA) offers smart factories an open, efficient and secure infrastructure for communications across various devices in the manufacturing process, including sensors, controllers and automation systems. OPC UA uses established computer industry standards, including IP and Web services, to enable devices to gather and convert data throughout the supply chain and across vendors.

Cybersecurity

With increased connectivity and communications, the risk of cyberattacks climbs. Unintentional breaches, industrial espionage and state-sponsored attacks can lead to unscheduled downtime, equipment interruptions and production disruptions. The ISASecure certification Embedded Device Security Assurance (EDSA) is one example of a security standard supporting smart manufacturing systems and devices. EDSA focuses on the security of embedded devices and addresses device characteristics and supplier development practices for smart devices. Devices that meet the requirements of the certification receive an industry stamp of approval for device safety.

Sustainability

In the long-term, not only do smart factories need to take efficiency and security into consideration, but sustainability should also be a top priority. Industry organizations such as the Smart Manufacturing Leadership Coalition are in the process of developing sustainability standards for smart factories. These standards focus on analyzing, simulating and optimizing sustainability performance of manufacturing systems. Sustainability is being tested and improved across material extraction, production, transportation, disposal, recycling and other steps of the manufacturing process.

All manufacturers are working toward a common goal – to make manufacturing safer and more efficient. As the smart manufacturing industry is projected to reach $246 billion by 2018, up from $156.2 billion in 2012, it can only continue this growth with global collaboration on standardization.

Reducing risk for industrial engineering workers

tariq.ahmad — Wed, 06 Oct 2021 20:53:00 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:53:00 PM

In March 2015, a 56-year-old line leader at Corsair Engineering Inc. suffered injuries while operating a powered industrial truck to flip over a fabricated metal automotive rack. As the rack was raised, the man backed up, causing the top tray to flip open and hit him in the back. After two weeks of medical care and attention, the worker passed away in April.

While every job poses potential risks, some are more dangerous than others. From industrial engineers on the factory floor to first responders such as firefighters and police officers, extra safety precautions must be taken to reduce the 4,679 workplace fatalities that occurred in 2014. Engineers at Honeywell and Intel teamed up to develop the Honeywell Connected Worker solution, a prototype for a wearable, IoT-enabled device aimed at improving workplace safety and increasing productivity.

Monitoring vital signs

In the midst of an emergency, a few seconds can be the difference between life and death. The Honeywell Connected Worker solution features a system called the Mobile Hub, which collects real-time sensor data on the user’s heart rate, breathing pattern, posture, motion and exposure to toxic gas. The data gathered is then displayed on a remote, cloud-based dashboard, giving plant managers and incident commanders the chance to better anticipate dangerous situations that may threaten the safety of workers.

Perhaps most importantly, the Honeywell Connected Worker solution enables users to produce a “man down” notification on the Mobile Hub dashboard by simply motioning his or her arm in a manner that is recognized by the system. The motion analysis makes it easy to pinpoint injured workers even in the most hazardous environments.

Improving speed and efficiency

By tracking the movement of factory workers and first responders, the same sensors used to protect employees from unexpected risks can also boost productivity. If, for example, a task takes a worker an unusually high number of steps to complete, the movement sensors can offer insight into what caused the loss in productivity. That information can later be used to develop training programs focused on increasing the speed at which workers perform specific tasks.

The Honeywell Connected Worker solution also measures heart rate, which is especially crucial when attempting to maximize the efficiency of employees in the workplace. Keeping a close eye on a worker’s level of exertion throughout the workday enables supervisors to avoid burnout by spacing out particularly exhausting tasks.

From 1994 to 2014, the number of fatal work injuries declined by nearly 30 percent. With the creation of the Connected Worker solution, engineers at Honeywell and Intel have taken a significant step toward dropping that number even lower. Engineers may never be able to prevent each and every workplace fatality, but that cer

Predictive maintenance in the IIoT

tariq.ahmad — Wed, 06 Oct 2021 20:53:00 GMT

Revision 1 posted to Documents by tariq.ahmad on 10/6/2021 8:53:00 PM

Below are just a few ways the IIoT is making this possible.

Risk analysis

Failure detection

Compliance

Manufacturers BYOD to the factory floor

tariq.ahmad — Wed, 06 Oct 2021 20:53:00 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:53:00 PM

Industrial automation is not a new concept to the manufacturing world, however, the Internet is. As the Internet of Things becomes a larger and larger phenomenon in almost every industry across the world, factory floors are gradually joining the trend by creating connected factory floors. With factory managers trying to optimize processes and lower costs, analytics tools could hold the key to improvement. Many manufacturing companies have taken the first step toward analytic tools by implementing “bring your own device” (BYOD) programs on the floor for more efficient operations.

According to a 2014 survey by IHS Technology, 46 percent of companies surveyed had already adopted or planned to adopt BYOD programs. These companies have found BYOD increases mobility and optimizes response time for engineers on the factory floor. It also brings economic advantages, as the majority of employees already own a smartphone or tablet, pay for their specific data plan and understand how to operate the device.

While these devices have proved successful thus far, many worry they are not designed to sustain the harsh conditions of the floor. To combat this, some manufacturing companies plan to replace commercial devices with company provisioned devices that are more durable.

An even larger concern for factory managers is that BYOD programs open the company to new avenues of vulnerability. When the company’s production system can be accessed from any location with just a few clicks on a tablet, hackers have a potential new point of access to the company’s data – a potential point many believe is not worth the risk.

Moving forward, each manufacturer will need to evaluate if a BYOD program is suitable to the particular company in question and if the advantages outweigh the security circumstances. If so, new techniques for protecting data exposure must be explored before complete adoption can be achieved.

Faster, better, stronger: industrial automation in America

tariq.ahmad — Wed, 06 Oct 2021 20:52:59 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:52:59 PM

The global industrial automation market is expected to more than double from $22 billion in 2014 to $48.9 billion in 2021. Three distinct trends – sustainability and efficiency, sophistication and data analytics – are driving faster development of industrial automation technologies, particularly in North America.

Given these trends, how is industrial automation improving and impacting various industries?

Sustainability and Efficiency

Industrial operations both large and small require long-lasting lines and lower impact power grids to be sustainable. The last thing manufacturers want is to frequently replace their systems, which ultimately slows down production. Manufacturers also need their lines to run with the highest level of efficiency and when they don’t run efficiently, to have the lowest down time possible. Most manufacturers in North America are running lean operations and those systems must be set up to survive in the long run with relative ease.

Sophistication

The industrial automation market is increasingly turning to sophisticated system applications within existing infrastructures. Manufacturers need sophisticated systems that include greater functionality and interoperability with what’s already in place. New levels of sophistication present manufacturers with a unique challenge – though the systems are advanced, the operators on the production lines are not necessarily any more available than in the past. For these systems that can do far more than was possible even just 3-5 years ago, their installation, maintenance and repair must be as simple as possible.

Data Analytics

While some might think the term “big data” is overused, this data is critically important to even the most minor changes in how production lines are run today. One example of data analytics in use is predictive maintenance, or using analytics to predict problems before they occur. This allows manufacturers to avoid interruptions in production and decrease the amount of down time on a production line. The implications of data analytics make a significant impact when it comes to efficiency. In production, time is money and predictive maintenance can decrease the amount of time needed to repair a line so it’s up and running right away – or doesn’t go down in the first place.

As sustainability, sophistication and data analytics improve development of industrial automation technology, the impact across industries can be a positive on. For example, the automotive and medical industries have significant opportunities to upgrade their production lines and increase efficiency on the floor, while industrial automation plants in the food and beverage industry decrease the amount of time needed to clean manufacturing lines. Industrial automation shows no signs of slowing down, which will ultimately bring increased efficiency and productivity to manufacturing across all industries.

Engineering safer industrial manufacturing

tariq.ahmad — Wed, 06 Oct 2021 20:52:59 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:52:59 PM

When it comes to industrial manufacturing, employee safety is just as important as productivity. In fact, injuries on the job have been a top concern since the height of the Industrial Revolution, when an average of one million workers were injured on the job each year at factories and manufacturing. While more stringent worker safety policies have since been put into place, engineers are constantly developing new technologies that put safety top-of-mind.

Overhead lifting systems

In a manufacturing environment, the choice of material handling equipment can have a significant impact on employee safety. The right equipment ensures workers don’t strain themselves or risk dropping those materials, causing both personal and material damage. Traditionally, most material handling equipment has consisted of on-floor movers such as trucks, forklifts and conveyor systems. These pose such risks as forklifts falling over due to unbalanced or heavy loads, poor visibility while driving forklifts and clothing or appendages getting caught in conveyor systems.

As an alternative to on-floor movers, engineers have developed overhead lifting systems, which improve safety and efficiency. These include cranes, hoists and monorails. Overhead lifting systems minimize the risk of overexertion, reduce injuries otherwise caused by falling materials and keep employees away from potentially dangerous machinery.

Wireless remote control systems
Industrial manufacturing facilities and individual machines are under constant pressure to improve efficiencies and as a result, workers must understand how updated equipment and processes impact safety. Over the past decade, one improvement has tackled both – wireless remote control systems. These systems offer increased mobility and reduced installation costs while ensuring operator and worker safety. For example, rather than operating a crane directly and risking injury or dropping heavy equipment, wireless remote control systems enable workers to operate cranes from up to 50 meters away without the inconvenience of cords.

Predictive maintenance

The Industrial Internet of Things (IIoT) serves many benefits when it comes to the productivity and automation of industrial maintenance. Preventative and predictive industrial maintenance in particular can decrease costs and unplanned downtime. However, productivity isn’t the only benefit – preventative maintenance also improves worker safety. By decreasing the chances of manufacturing equipment going down on the job, employees are less likely to suffer from injuries associated with equipment malfunctions. The IIoT also automates certain tasks, such as those that pose the most risk to industrial manufacturing workers, further mitigating risks.

Manufacturing safety has come a long way since the Industrial Revolution, but there’s always room for improvement. The U.S. Department of Labor Statistics reports “day away from work” injuries in manufacturing increased 5 percent in 2014. As industrial manufacturing increasingly prioritizes safety as much as efficiency, engineers will develop more ways to protect workers on the job and decrease the number of injuries.

A look inside the factory of the future

tariq.ahmad — Wed, 06 Oct 2021 20:52:59 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:52:59 PM

The first Industrial Revolution launched the phenomenon of mass production and the second Industrial Revolution launched the miracle of electricity. Today, with the help of the Internet of Things and new technologies, engineers are making inroads in launching the next industrial revolution, beginning with the factory of the future.

The idea behind the factory of the future is to bring research and advanced automation technologies into the production environment to develop new manufacturing processes and systems. Research groups around the world are on the hunt for these innovations that will shape the third industrial revolution.

Research hubs have emerged around the world with the means to experiment with digital technologies and manufacturing machinery. Their objective is simple: to create the new infrastructure of production.

On Chicago’s Goose Island, the Digital Manufacturing and Design Innovation Institute is developing an operating system for cyberphysical manufacturing as well as a communications framework for intelligent machines.

In Australia, Swineburne University of Technology’s Advanced Manufacturing and Design Center is giving undergraduate students access to design, manufacturing, machining, innovation and research efficiency studios to produce prototypes.

Meanwhile in Chemnitz, Germany, a hub simply named Factory of the Future is focused on redefining the role of humans in factories.

Popular Concepts

While hundreds of concepts are being studied at these hubs, there are a handful of popular concepts being tested across the industry.

Virtual reality

Virtual reality is being used in the early stages of design to create training environments for engineers to test new systems. Chemnitz’s Factory of the Future utilizes VR technology to simulate a factory setting that employees can view and explore. When the technology detects head movement it switches the view of the factory accordingly throughout the experience.

Automation

In addition to production and packaging, automated logistics operations are the focus of many robotic initiatives, including Pan Robots, where engineers are using on-board cameras, laser scanners, 3D maps, and intelligent systems to improve a variety of warehouse procedures.

New materials

Engineers are exploring new product properties using innovative materials, like nanoparticles in the medical field. As nanotechnology finds a new home in pharmaceutical factories, nanoparticles could soon play a significant role in developing new methods of drug delivery and diagnosis.

Sustainability

Engineers are devising new ways for future factories to incorporate sustainable methods for repurposing waste. For example, a factory that produces sugar beet products in Norfolk, England has begun using heat waste to warm a greenhouse and carbon-monoxide emissions to aid in photosynthesis.

The Future of Industrial Engineering

With nearly 300,000 factories in the U.S. alone, it’s clear that introducing new manufacturing processes to the industry will not happen quickly. However, once adopted, these new processes will clear the path for more efficient, structured and organized manufacturing. As these fast-paced factories become more digitally connected, they will be capable of collecting higher volumes of data in the transfer of information to all areas across the supply chain. In addition, the streamlined processes will lead to a more advanced value chain and a more skilled workforce.

As engineers carry us into the third Industrial Revolution, manufacturing and warehouse facilities around the world will see advanced processes, streamlined operations and new technologies fit for a factory of the future.

3 technologies changing industrial engineering

tariq.ahmad — Wed, 06 Oct 2021 20:52:58 GMT

Current Revision posted to Documents by tariq.ahmad on 10/6/2021 8:52:58 PM

Advancements in technology are making industries smarter and faster each day and industrial engineering is no exception. The centuries old profession has seen countless improvements since the first Industrial Revolution, but the cyber and physical systems controlling the next revolution are certain to triumph over those of the past.

Below are three of the top technologies changing industrial engineering as we know it:

Automation and the IIoT

Buzz of the next Industrial Revolution is centered around automation. Modern manufacturing and automation are paving the way for leaner processes by increasing productivity and decreasing spending. Aiding in the development of those leaner processes is the Internet of Things. Connected devices are transforming industrial engineering with new capabilities that allow engineers to remotely operate machinery, gather data and communicate information from the cloud.

The process of adding a software component to traditional manufacturing, titled the Industrial Internet of Things, has already found success in smart factories around the world. For example, Intel reported connecting equipment to the cloud improved their hardware product reliability twofold.

3D Printing

3D printing adoption has become increasingly popular over the last year and it doesn’t show signs of stopping. According to a recent survey on 3D printing adoption by Sculpteo nearly half of respondents plan to increase additive manufacturing by 50 percent by 2016. With the ability to accelerate product development, create prototypes and offer custom or limited-time products, 3D printing provides increased industrial efficiency at a low cost. It also does not require the production of new tools required for traditional manufacturing, therefore eliminating even more costs and lead times.

The efficiency and cost-effectiveness offered by 3D printing is impacting a number of industries including aerospace, medical and transportation. For instance, Boeing and General Electric are collaborating on a process to include 3D-printed parts in commercial jet engines.

Software Programs

An issue that’s often overlooked when talking about the latest industrial revolution is cost. Although using connected devices and 3D printing lowers costs to an extent, extensive cost analysis is still required and is often too expensive of an undertaking for manufacturers to outsource. To combat these expenses, companies are using software programs as a new source of cost management.

With CAD interpretation, software programs use custom algorithms to generate cost analyses for different products. Engineers have the option to filter the results based on material, time for assembly, mold and much more.

Some of these product cost management software programs offer additional functionalities to help companies make better-informed purchasing decisions. For example, aPriori offers online education services that provide customers with the tools to develop successful product cost management strategies.

The introduction of these new technologies has played a major role in the evolution of industrial engineering, making factories smarter and more efficient than ever before. With the launch of the next industrial revolution just around the corner, engineers can expect to see more technological advancements shape the industry and their role in the future.

Documents

migration.user — Fri, 01 Oct 2021 18:04:57 GMT

Current Revision posted to Documents by migration.user on 10/1/2021 6:04:57 PM

The Basics of Distance-Based Photoelectric Sensors

rscasny — Sun, 11 Sep 2016 14:26:33 GMT

Current Revision posted to Documents by rscasny on 9/11/2016 2:26:33 PM

Photoelectric sensors that only detect the presence or absence of an object may not be appropriate for every application. As a result, a variety of distance-based photoelectric sensors have been developed to address more challenging application requirements. Distance-based photoelectric sensors not only determine the presence of an object, they also determine its position. Three methods have emerged as front-runners of distance-based photoelectric sensing, which will be covered in this blog.

Background suppression (BGS)

The oldest and simplest method is called background suppression, or BGS. BGS sensors detect based on the triangulation of light that is reflected from an object back to the sensor’s receiver. Light from the sensor is reflected at different angles based on the distance the object is from the sensor. When something is close to the sensor, the angle is larger than when something is farther away. And because the angle of the reflected light changes, it results in the light reaching different parts of the sensor’s receiver.

Multipixel array (MPA)

While BGS has been in existence for several decades, a newer technology has emerged as an outgrowth of BGS. Multipixel array (or MPA) products are based on a variation of BGS technology. In both BGS and MPA photoelectricsensors, the sensor emits light, which is reflected by an object back to the sensor’s light-sensitive receiver area. And the triangulation of that reflected light determines where it contacts the receiver, which is then used to determine distance. But the difference between the two is that a BGS sensor uses two receiver elements, while an MPA sensor uses more than that number of receiver elements, often over 100 receiver elements per array.

One sensing threshold is set for a BGS sensor. The threshold is determined by the distance at which more of the reflected light begins to fall on the “near” element receiver rather than the “far” element receiver. However, in an MPA sensor, the distance-based sensing is determined by where on the receiver array the majority of the reflected light is centered. With MPA sensors, multiple switching thresholds or windows are possible for more complex application requirements. MPA also offers a higher level of control and configuration than BGS models because there are more configuration options available. Unlike BGS with just one distance threshold, now it is possible to set multiple simultaneous thresholds or even sensing windows with user-defined minimum and maximum sensing distances. Because both BGS and MPA sensors detect where light is reflected instead of how much light is reflected—as is the case with conventional sensors—they are also remarkably insensitive to variations of objects’ reflectivity or color.

Pulse Ranging Technology (PRT)

Pulse Ranging Technology (PRT) sensors are either diffuse, meaning they emit light that is reflected from the object to be sensed back to the sensor’s receiver, or retro-reflective, meaning they emit light that is reflected from a corner-cube reflector back to the sensor’s receiver. But unlike the previous two technologies, PRT technology uses only one receiver element. A timer in the sensor determines how long it takes—after it emits a short burst of light—for the light to make it from the sensor to the object and then be reflected back to the sensor again. Calculating this time duration and using the speed of light in air as a constant then determines the distance from the sensor to the object.

PRT is true “time of flight” (TOF) distance measurement. It is critical to note that the term “time of flight” is often misused in industry, as some manufacturers improperly use it to describe a different method of distance measurement that is more accurately called phase correlation or is chip-based technology. In phase correlation distance measurement, the reflected light is evaluated at the receiver, not based on the time it took to get from the sensor’s emitter to the object and be reflected back, but rather by how much the phase angle of the light shifted as it traveled to and from the object. In other words, phase correlation geometrically calculates the distance rather than accurately measuring it, as is the case with PRT.

But phase correlation distance measurement has significant disadvantages compared to PRT distance measurement. Phase correlation sensors have a weaker LED intensity since they are continuously on, resulting in shorter sensing distances and difficulty detecting dark objects. They are also limited to short sensing ranges because they detect shifts to the reflected light’s phase angle, but anything greater than 360° can be misinterpreted by the sensor. This also means they are prone to detecting background objects, especially those that reflect light at the same phase angle as light in the sensing range. For example, whether reflected light is shifted in phase by 90° or by 450°, there is no way for a phase correlation sensor to differentiate the two. This results in the detection of “phantom objects” in the background. Other strengths of PRT include its ability to ignore environmental conditions such as ambient light, temperature, and target color, and that measured values don’t drift as they do in phase correlation, even after prolonged use.

For more information on distance-based photoelectric sensors, please download the attached pdf by Pepperl + Fuchs, called "Technical Considerations for Selecting Distance-based Photoelectric Sensors," which was the source for this document.

Attachments:

community.element14.com/.../tdoctb0c2_5F005F00_eng.pdf	tdoctb0c2__eng.pdf
community.element14.com/.../PEPPERL_2B00_FUCHS--3RG7404_2D00_7CH00_2D00_PF--PHOTO-SENSOR.pdf	PEPPERL+FUCHS 3RG7404-7CH00-PF PHOTO SENSOR.pdf

Tags: background suppression, pulse ranging technology, 3rg7404-7ch00-pf, multipixel array, pepperl + fuchs, series k20, 2501164, 20t8442, distance-based photoelectric sensors

The Basics of Piezoresisitive and Foil-Based Pressure Sensors

rscasny — Wed, 24 Aug 2016 22:55:38 GMT

Current Revision posted to Documents by rscasny on 8/24/2016 10:55:38 PM

Pressure is the force per unit area exerted by a fluid or gas. The recognized International System of Units (SI) for pressure measurement is the Pascal (Pa); however, pounds per square inch (psi), inches f water (in-H₂O), Newtons per millimeter squared (N/mm²) and Bar are also common. The most critical mechanical component in any pressure transducer is generally the pressure sensing structure (spring element). The pressure of the fluid or gas is a force on the pressure sensing structure. The function of the structure is to serve as the reaction for this applied force; and, in doing so, to focus the effect of the force into an isolated uniform strain field where strain gages can be placed for pressure measurement. While there are various types of pressure sensing technologies, two will be discussed in this paper: Piezoresistive-Type Pressure and Foil-Based Pressure.

Piezoresistive-Type Pressure Sensors

In piezoresistive-type pressure sensors, the transduction elements, which convert the stress from the diaphragm deflection into an electrical signal, are called piezoresistors. Piezoresistance equals changing electrical resistance due to mechanical stress. The pressure sensing element is a diaphragm which is made from silicon. This silicon diaphragm is attached to a glass substructure (i.e., that acts as a constraint/mounting structure for the silicon). This silicon diaphragm structure performs in a predictable and repeatable manner as the pressure is applied (i.e., a very slight deflection in the structure). This pressure is translated into a signal voltage by the resistance change of the strain gages which are doped (i.e., implanted) onto the silicon diaphragm surface, then organized in an electrical circuit.

The silicon diaphragm, with the exposed doped Wheatstone Bridge, in test and measurement pressure sensors, is isolated from the pressure media being measured (i.e., media isolated pressure sensors). This is achieved by creating a cavity between the media being measured and the silicon diaphragm, then filling it with oil that does not attack the silicon or electrical circuit. On the opposite side of the cavity is a metal/steel diaphragm that is flexible to transmit the pressure being measured to the oil in the cavity, and the silicon diaphragm. This metal/steel diaphragm is called the isolating diaphragm.

At a very top level, this technology can be described as a pressure sensor consisting of a micro-machined silicon diaphragm with piezoresistive strain gages diffused into it, fused to a silicon or glass back plate. Pressure induced strain increases or decreases the value of the resistors (i.e., strain gages). This resistance change can be as high as 30 %, that typically yields one of the higher outputs from a pressure sensing technology. The resistors are connected as a Wheatstone Bridge, and the output of which is directly proportional to the pressure.

Foil-Based Pressure Sensors

Another common type of pressure sensor utilizes a bonded foil strain gage to measure an applied pressure in one of two ways. In some models, such as miniature pressure sensors, foil strain gages are bonded to the back of a steel diaphragm that is exposed to the media being measured. The diaphragm structure performs in a predictable and repeatable manner as the pressure is applied (i.e., a very slight deflection in the structure). This pressure is translated into a signal voltage by the resistance change of the strain gages, arranged strategically around the diaphragm surface, and is organized in an electrical circuit.

However, in many other models, the foil strain gages are bonded to an element that is mechanically connected to a diaphragm, then exposed to the media being measured. The strain gaged element is measuring the force transmitted from the diaphragm by the mechanical linkage. This element acts as a load cell (i.e., designed to measure force that is directly proportional to the load applied to the diaphragm).

To learn more about Piezoresistive and Foil-Based Pressure Sensors, please download the attached document by Honeywell Sensing and Control called "Effectively Using Pressure, Load, and Torque Sensors with Today’s Data Acquisition Systems," which was the source of information for this document.

Attachments:

community.element14.com/.../White_5F00_Paper_5F00_EffectivelyUsingPressureLoadandTorqueSensorswithTodaysDataAcqusitionSystems_5F00_008883_2D00_2_2D00_EN.pdf

White_Paper_EffectivelyUsingPressureLoadandTorqueSensorswithTodaysDataAcqusitionSystems_008883-2-EN.pdf

Tags: hscdann010bgaa5, mechanical stress, piezoresistive pressure sensors, 90r7899, 29y6981, foil-based pressure sensors, honeywell, strain gages, bonded foil strain gage, pressure transducers, 060-0743-11tjg, silicon diaphragm, wheatston bridge

4 Tips For Selecting the Correct Hall-Effect Sensor for Brushless DC Motors

rscasny — Wed, 17 Aug 2016 21:13:23 GMT

Current Revision posted to Documents by rscasny on 8/17/2016 9:13:23 PM

Brushless dc (BLDC) motors need to operate more efficiently as energy and cost savings becomes a bigger concern for designers of electronic devices. One way to help ensure greater efficiency is by selecting the correct bipolar latching Hall-effect sensor IC for electronic commutation in BLDC motors. These tiny ICs play a big role in motor efficiency, which can significantly affect the reliability and performance of many critical applications, including robotics, portable medical equipment and HVAC fans.

BLDC Motors: A Backgrounder

BLDC motors use electronic instead of mechanical commutation to control the power distribution to the motor. Latching Hall effect sensors, mounted in the motor, are used to measure the motor’s position, which is communicated to the electronic controller to spin the motor at the right time and right orientation.

These Hall effect sensors are operated by a magnetic field from a permanent magnet or an electromagnet, responding to South (operate) and North (release) poles. These magnetic sensors determine when the current should be applied to the motor coils to make the magnets rotate at the right orientation.

There are several design characteristics that BLDC motor manufacturers should evaluate when selecting a bipolar latching Hall effect sensor to commutate the motor so it can operate as efficiently as possible. These include sensitivity, repeatability, stability-over-temperature, and response time.

Tip #1: Sensitivity

A magnetic field is required to activate a Hall-effect sensor. Sensitivity level is based on the placement of the sensor to the magnet, the air gap, and magnet strength. Product datasheets should indicate the magnetic field strength (measured in Gauss), required to make a bipolar Hall effect sensor change state (operate and release). A high sensitivity sensor, typically rated at less than 60 Gauss, allows for the use of smaller magnets or less expensive magnetic materials, increasingly important as the prices for rare earth magnets continues to increase.

High sensitivity also allows for a wider air gap, which means the sensor can be placed further away from the magnet and still be very reliable, while providing some design flexibility. Or given the same air gap, the sensor is more sensitive, thus delivering higher reliability and repeatability. This means a Hall-effect sensor with high sensitivity or a lower magnetic switch point delivers more efficient motor performance.

Tip #2: Repeatability

Repeatability refers to the Hall-effect sensor’s latching time. It goes hand-in-hand with high sensitivity, as it allows the sensor to be more repeatable. When the sensor output turns on, it directs current through the coil windings in the stationary part of the motor. This current produces a magnetic field that interacts with the field from the permanent magnets on the shaft and causes the shaft to spin. As the magnet rotates past the sensor, a highly repeatable sensor changes state at the same angular position each time the magnet passes by. For example, one complete revolution of the motor shaft is 360 degrees. If the sensor turns on at five degrees when the shift spins the first time, does it change state at five degrees at the next rotation? A highly repeatable sensor is one that has a consistent response time, which will maintain all of the angular measurements very close to the same value. In this case, at five degrees.

Why is this important? To produce the maximum amount of torque on the shaft, the timing between current flowing through the coil and the position of the shaft must be as accurate as possible. If there is a delay in the sensor’s response to changes in the magnetic field, this slower response can lead to lower bandwidth and accuracy errors. Any error in the switching point of the Hall-effect sensor will reduce the torque of the motor, which results in lower motor efficiency.

Tip #3: Stability

Similar to repeatability, stability refers to how much the angular position changes, but in this case, versus temperature or voltage. For example, if the sensor output changes state at five degrees at 25 °C, where does it change state at 125 °C? The Gauss level required to turn a part on at 125 °C needs to be as close as possible to the Gauss level required to turn a part on at 25 °C. So, if a part operates at 30 Gauss at 25 °C, does it operate around 30 Gauss at 125 °C, or does the operate point shift to, for example, 50 Gauss or 5 Gauss?

Honeywell Sensing and Control’s SS360NT high sensitivity bipolar latch Hall-effect sensor has operate and release points that are nearly magnetically symmetrical over the operating temperature range. This means a sensor operating at positive 30 Gauss will release at approximately negative 30 Gauss. This is important because stability-over-temperature, coupled with high sensitivity, is needed for precise position detection. Magnetic stability also helps improve jitter performance, which is critical for BLDC efficiency, and results in less speed variation.

Tip #4 Response Time

Response time is the time it takes for the output of the sensor to change state. For example, if a sensor has an operating point of 30 Gauss, and a 30 Gauss magnetic field level is applied to the sensor, the response time is measured from the point when the 30 Gauss field is applied to when the output changes state. A faster response time to a change in the magnetic field delivers greater efficiency in commutating a BLDC.

If a sensor switches at a different magnetic field level than what is required due to slow response or delay, this could result in accuracy errors. Motors need to switch at a very specific point to achieve the highest efficiency. Mis-commutation results in lower effective torque constant (Kt) and higher torque ripple that can cause additional noise as well as impact efficiency and system performance.

Don’t underestimate the value of Hall-effect sensors in BLDC designs. These tiny devices shouldn’t be an afterthought during the design process as they have a big impact on motor efficiency. Designers need to look closely at several specifications including sensitivity (60 Gauss rating or less), repeatability (changes state at the same angular position each time the magnet passes by), stability (operate and release points virtually symmetrical over the temperature range), and response time (switching as close to the change in the magnetic field level).

To learn more about Hall-Effect Sensors for BLDC motors, please download the attached document by Honeywell Sensing and Control called "How to select Hall-effect sensors for brushless dc motors," which was the source of information for this document.

Attachments:

community.element14.com/.../Honeywell-Select_2D00_Brushless_2D00_dc_2D00_Motors.pdf

Honeywell Select-Brushless-dc-Motors.pdf

Tags: brushless dc motors, response time, 69w6714, sensitivity, ss360nt, mis-commutation, high sensitivity bipolar latch hall-effect sensor, repeatability, bldc motors, stability, hall effect snsors, electronic commutation

Designing Programmable Logic Controllers (PLCs) with SoC FPGAs for Industry 4.0

rscasny — Fri, 12 Aug 2016 20:34:10 GMT

Current Revision posted to Documents by rscasny on 8/12/2016 8:34:10 PM

Programmable logic controllers (PLCs) are an integral part of factory automation and industrial process control. PLCs control a variety of analog and digital sensors and actuators, and communicate over simple to complex interfaces in varying protocols. In addition to control functions, PLCs perform signal processing and data conversion. But in the future, PLCs, driven by developments in the Industrial Internet of Things (IIoT), will deliver scalable solutions that are secure, high performance, low power, small footprint, and are ready for Industry 4.0 with built-in secure communications to enterprise IT systems.

Backgrounder on PLCs

Since their introduction a few decades ago, PLCs have evolved from simple input-output controllers to complete processor-based systems that execute complex control algorithms. But PLCs have undergone significant form-factor changes over the years from industrial PCs and Programmable Automation Controllers (PAC) in PC-like form-factors to compact enclosures and mini-PLCs. The scope of PLC functionality has also evolved. In addition to discrete control functions, PLCs have integrated functionality such as Human Machine Interface (HMI), motion-control, real-time industrial Ethernet, and data communication gateways.

The demand for additional features, precision, and connectivity on the factory floor has driven the increasing integration of PLCs and its associated technologies. It has been sustained by PLC component cost reductions and the availability of higher performance processing engines. In general, the evolution of PLC functionality has followed the industrial automation demand curves of features, performance, and lower power. Following that trajectory, the demands of Industry 4.0 and IoT, to a large measure, will drive future PLC architectures.

Challenges of PLC Design Today

The current manufacturing automation environment of Industry 4.0 demands high performance PLCs enabled with secure enterprise connectivity and HMI. Today, multiple international Industry 4.0 initiatives rely on cyber-physical systems to implement the promise of smart manufacturing, leveraging connected systems for Machine-to-Machine (M2M) and enterprise interaction. Making PLCs ready for Industry 4.0 is fraught with new challenges, requiring grounds-up PLC redesign. The major challenges confronting PLC designers today include:

High-performance control: Smart-manufacturing environments require PLCs to process instructions, service interrupts, and support integrated HMI at speeds faster than ever before. This need has led to the use of more powerful processors with higher MIPS and multiple cores, resulting in high cost and power consumption penalties.
Connectivity: Deterministic M2M connectivity between disparate machines requires support for multiple Industrial Ethernet protocols (including newly emerging standards-based deterministic Ethernet such as IEEE 802.1 TSN) within a single PLC system. Enterprise connectivity demands application interoperability frameworks such as OPC-UA.
Secure communications: PLCs connected outside the factory network and to the enterprise are vulnerable to cyber-attacks, making security a significant concern.
Cross-platform interoperability: Choosing the wrong processor or ASSP can be an expensive error. Functional interoperability between diverse systems requires standardized operating systems running on non-proprietary processor cores.
Future proofing: With an ever-evolving connectivity and interoperability environment, changes in market requirements are more frequent, leading to software and hardware changes.

PLC Design with SoC FPGAs for Industry 4.0

System-on-Chip (SoC) FPGAs, which combine a processor and FPGA fabric on a single chip, present a unique alternative for overcoming today’s PLC design challenges. Manufacturers who use SoCs in PLC architectures can derive the following benefits:

High performance
4,600 DMIPs for less than 1.8 W
Up to 1,600 GMACs and 300 GFLOPS based on >125 Gbps processor to FPGA inter-connect and cache coherent hardware accelerators
Lower power—Up to 30% less power vs. a two-chip discrete solution
Reduced BOM and PCB space and layer cost—Up to a 55% form factor reduction
Scalability and investment protection—Scalable SoC processor roadmap grows with application needs and protects software development investment
Flexibility—SoC FPGAs can accommodate software and hardware changes
Improved time to market

To learn more about PLC design using SoC FPGAs, please download the attached document by Altera, called "PLC Architecture in the Industry 4.0 World," which was the source of information for this document.

Attachments:

community.element14.com/.../Altera-_2D00_-PLC-Architecture-in-the-Industry-4.0-World.pdf

Altera - PLC Architecture in the Industry 4.0 World.pdf

Tags: industry 4.0, plc, plc architecture, soc, programmable logic controllers, system on a chip, fpga, cyclone v, automation controller, altera