- By Jack Smith
- November 06, 2024
- InTech Magazine
- Feature
Summary
Users need guidance to deploy sensors appropriately. A new standard may be the answer.
The dictionary defines automation as “the technique of making an apparatus, a process or a system operate automatically.” ISA, the International Society of Automation, defines automation as “the creation and application of technology to monitor and control the production and delivery of products and services.”
Using ISA’s definition, the automation profession includes “everyone involved in the creation and application of technology to monitor and control the production and delivery of products and services.” An automation professional is “any individual involved in the creation and application of technology to monitor and control the production and delivery of products and services.”
During an ISA meeting where automation concepts were being discussed, Dennis Brandl, chief consultant at BR&L Consulting recommended that the term “total automation” be used to differentiate it from Hyperautomation. Brandl formally presented total automation at COPERMAN 2023. The Conference on Performance and Management (COPERMAN) aims to bring together researchers and practitioners to present and discuss innovative contributions concerning the measurement and management of organizational performance in a modern business environment.
Total automation is an important aspect of digital transformation because it serves to use information technology/operational technology (IT/OT) to improve performance for dangerous, dirty, demanding, delicate, and dull tasks (the five Ds of manufacturing).
The importance of total automation
According to Brandl, total automation is “a disciplined and all-inclusive approach to the entire process automation strategy of a manufacturing enterprise.” He said total automation is the next step beyond Hyperautomation, which he explained as an IT initiative to increase the automation of business processes (production chains, workflows, marketing processes, etc.) by introducing artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA). “Total automation applies the concepts of automation to all elements of a company including OT and IT. The goal is to reduce the human errors that crop up in manual processes, and to use computing resources to verify and validate business operations,” he said.
Brandl said that total automation allows for performance management of all activities in a manufacturing enterprise. It is the combination of IT Hyperautomation, process automation, sensor automation, and OT task automation. Another way to look at it is by using new technologies in a real-time environment.
“The objective of total automation is to completely automate the processes in an operational facility to increase efficiency and productivity and reduce errors,” said Steve Mustard, president and CEO at National Automation Inc. and former (2021) ISA president. “Even with advances in technology over the past few decades, many organizations continue to operate manual or semi-manual processes. Examples include the manual collection of sensor readings, manual data entry, and manual analysis of data.
“The concept is important now as organizations seek to squeeze out every last drop of efficiency from their operations so they can be competitive in the global marketplace, responsive to changing customer demands, and be resilient to inevitable supply chain disruptions.”
Mustard described the automation/manufacturing timeline. The first industrial revolution of the 1800s transitioned processes in labor-intensive industries such as mining and textiles. The second industrial revolution in the 1900s introduced the internal combustion engine and electrification, enabling mass production. The third industrial revolution saw the rise of computers and telecommunications enabling greater automation and digitalization. “The fourth industrial revolution, or Industry 4.0,” explained Mustard, “builds on these advances and seeks to reshape how industries operate through the use of disruptive technologies such as AI, big data, and IIoT [Industrial Internet of Things]. Total automation leverages the disruptive technologies of Industry 4.0 to transform how organizations operate.”
Mustard shared some examples of the use of these technologies to move toward total automation:
- Using ML to automatically analyze images to detect corrosion or other defects to reduce the time and effort involved in manual analysis and improve accuracy and reliability by the removal of human bias.
- Using IIoT to automatically collect sensor data to remove the need for manual data collection.
- Using AI to analyze sensor data to look for patterns that are not obvious to humans to reduce unplanned downtime.
The need for a total automation standard
The industry already has ISA95. But how would a total automation standard fit the various levels of the ISA95 model?
According to Mustard, total automation applies to all ISA95 levels:
- Level 1: Use of IIoT to collect remote sensor data; use of AI or ML to maintain calibration and report on sensor discrepancies.
- Level 2: Use of AI in expert systems supporting operator decision making.
- Level 3: Use of AI to optimize production schedules and analyze machinery health.
- Level 4: Use of big data analytics, AI, and cloud to automate business decision making.
“Through all layers, the objective of total automation is to use disruptive technology to streamline and automate all processes,” Mustard said.
Brandl agrees that a total automation standard would apply to all layers of the ISA 95 model (Figure 1). “Layer 2 is covered by existing ISA and automation standards. Layer 1 is partially covered by the standards on maintenance and security (automated calibration, automated cleaning, automated alignment, automated error detection, etc.). Layer 3 is mostly covered by ISA 99, 95, and 88. The concept of interoperable distributed workflows helps fill in some of the missing pieces, in my opinion,” he said.
Brandl and Mustard support the proposal of a new standard, or at least a revision to, or expansion of an existing standard. Jonas Berge, senior director of Applied Technology at Emerson in Singapore, submitted a justification for the evaluation of such a standard.
According to Berge, users need guidance in deploying sensors appropriately throughout their plants. “However, there are many equipment categories to cover and if we try add sensors to everything, we will never finish. A good start would be common asset types like pumps and heat exchangers found in all plants. More equipment types and other positions could be included in subsequent revisions or other sections. We could start with common asset types like pumps and heat exchangers found in all plants. More equipment types and other positions can [be included In] subsequent revisions or other sections.”
Whether total automation, digital transformation, Industry 4.0, or IIoT, getting real-time data begins with the sensors. “Users don’t always know what to sense, what sensors are required on each equipment type, what mechanical gauges should be replaced by sensors, where submetering is required, or what update period to set,” explained Berge. “A standard could help plants—especially process plants. It would also make ISA more relevant in the digital transformation/Industry 4.0 megatrend.”
Berge said that there seems to be a gap in our standards in that we provide little to guide people in identifying, selecting, and validating sensing opportunities. “Some examples may repurpose the data from existing sensors, while others require new sensors. For the former, it is critical that the additional dependencies be documented. If data is already being gathered by the control system, perhaps get it from them,” he said.
There are not any existing standards that are relevant to the use of this technology, or that must be followed in its application, according to Berge’s justification. “It could be somewhat related to ASME PTC, which defines equations using data because the proposed standard will help users get the right data. API670 is limited to vibration. The proposed standard would be far broader in scope because it would automate all manual measurements (automate corrosion, acoustic noise [leaks], mechanical gauges, and clipboards). API682 is limited to pump seals. The [proposed] standard would be far broader in scope,” he said.
“There are not really any models or other architecture-related information that helps to understand the technology and its application,” Burge said. “The standard would recommend sensors—not how these sensors are architecturally connected. These are sensors ‘beyond the P&ID’—not for process monitoring or control.
This would be related to the NAMUR NE175 standard; it is for equipment performance and condition monitoring. In addition, it would also be related to sustainability like energy management, WAGES [water, air, gas, electric and steam] submetering for EMIS, and emissions monitoring like relief valves, flaring, and methane. It would also support equipment performance monitoring. It would also fit nicely in the various layers in the ISA95 model. There are not really any other technologies related to a proposed total automation standard. The standard should recommend what sensors to deploy on each type of equipment and in other places. It would not define sensor or signal transmission. However, most sensors will be wireless using IEC62591 or other methods.”
The technology behind a proposed total automation standard drives functionality, which enables how it would be applied. Application areas include (but are not limited to):
- Reliability/maintenance of rotating equipment, valves, etc.
- Integrity (corrosion/erosion) of piping and vessels.
- Safety (including health and environment): safety showers, manual valves, etc.
- Production/quality would require sensors in place of mechanical gauges.
The technology that supports a proposed standard does not define an architecture per se. It does, however, imply a definite increased sensor count—more sensors in existing architectures. Sensors are selected, installed, configured, and supported by instrument and control personnel, many of whom are members of ISA, according to Bergeee.
In addition, this standard will make plants more sustainable. By using the appropriate sensors, collected data would detect and pinpoint energy overconsumption, emissions, and equipment inefficiency. It could monitor cleaning optimization and help reduce flaring. Downtime would be reduced due to more predictive maintenance, failure prediction, and reduced loss of containment. Plants will be safer because of reduced human error, and fewer manual valves and leaks. Finally, automating existing manual data collection will enable plants to be more productive.
Looking ahead
Brandl said the concept of a “digital companion” has started in the medical field. A digital companion provides personalized assistance. “We need a digital assistant for everyone performing manufacturing operations management tasks, either on the shop floor or in the production back office. A digital assistant that looks over your shoulder would manage your tasks, make reminders, bring up relevant information, record completions, walk you through manual steps in processes, and collect information from equipment; it is truly mobile. We already have a name for it: Manufacturing operations management [MOM]. But it’s your personal MOM, loaded with your tasks and schedules,” he said.
Brandl advocates performance management—measuring and improving individual processes—for all activities. “Personal productivity effectiveness (PPE) is the human equivalent of overall equipment effectiveness (OEE),” he said.
Standards require consensus. With so many things to gain, and nothing to lose, total automation stands to take automated manufacturing to the next level.
This feature originally appeared in the October 2024 issue of InTech digital magazine.
About The Author
Jack Smith is senior contributing editor for Automation.com and InTech digital magazine, publications of ISA, the International Society of Automation. Jack is a senior member of ISA, as well as a member of IEEE. He has an AAS in Electrical/Electronic Engineering and experience in instrumentation, closed loop control, PLCs, complex automated test systems, and test system design. Jack also has more than 20 years of experience as a journalist covering process, discrete, and hybrid technologies.
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