Plant IT: Integrating Information Technology into Automated Manufacturing

Integrated Plant Performance Management as a Means to Improve Profitability

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And, to be successfully implemented, companies will also have to change their cultures and organizational structures as they nurture a new united workforce. With the wall crumbling, there are requirements for hybrid competencies. Though McElroy Metal hired someone with dual expertise, they are not focusing on one person who can do it all—instead they are focusing on a team of people who are exposed to the cross-functional requirements and who work collaboratively within the system integration group.

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They are also working on bringing data produced by the shop floor controllers back to the ERP system for reporting purposes. Leading these integration efforts are two people who are supported by the entire IT department. Sometimes the right people come in the form of third-party control system integrators, since these folks are on the front lines of the IT infiltration of the factory floor.

More and more, manufacturing customers ask system integrators to handle hardware, software and network requirements in addition to automation integration.

April 2016

In addition, to keep the OT analysts up-to-date, these individuals also support the IT infrastructure within Bachelor Controls. PDA not only goes to the client site to automate and integrate systems, but the company brings its clients back to its new SCADA Lab—built in the past few months and complete with a mock factory—to teach them about anything they want to know, from Ethernet switches to cybersecurity.

With Ethernet as the backbone between the office and the factory floor, as well as giant servers with virtualization software and thin clients populating the plant, there is no clear line of demarcation between the IT data guys and the OT process people. Automation vendors are reacting to this occupational shift by creating products that offer a richer user experience, appealing to emerging IT skillsets on the factory floor. In the past, people would compare product features, but now it is about allowing users to get up and running quickly by providing an interface that is different than the typical industrial design, he says.

GE understands the manufacturing IT dilemma that companies face, since GE faces the same issues internally. The organizational shift that GE is making is something every manufacturer should consider to prepare for the future workforce. As a consequence, usability will become a key design consideration in future OT products. The arrival of Millennials into the workforce is actually a boon for companies trying to fuse IT and OT skillsets because they have grown up with technology.

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Smith encourages his students to leverage their smartphones as educational tools. Similarly, Wichita Technical Institute in Kansas has developed an month integrated electronics program that includes industrial controls and networking. The school is looking at increasing the length of the electronics program and integrating an IT class because of the mixed technology emerging in manufacturing, says campus director Rod Moore.

Identifying a need for continuing education while on the job, IT and automation vendors are beginning to collaborate on new training and certification programs, too. Last year, Cisco and Rockwell Automation jointly rolled out the Managing Industrial Networks with Cisco Networking Technologies training course and the Cisco Industrial Networking Specialist certification to provide foundational skills. It is a communication and culture connection, he says.

Book Review: IT and Automated Manufacturing

This group will address the projected skills gap of 2 million trained engineers who will need specialized IoT training in the next decade. In addition, the consortium will focus on the fact that college graduates lack the skills to fill new jobs because of curriculum gaps in areas like IoT, analytics and cybercrime.

These new educational movements will likely translate into new kinds of jobs. Adding to these challenges, the experience and competency needed to manually align with high-level objectives are declining due to retirement of key personnel, especially control room operators.

What if KPIs could be structured systematically across an organization from management through engineering to operations to unify all the employees' capabilities, motivate them to do better, and cultivate the knowledge in the DNA of the organization? Yokogawa collaborated closely with KBC industry consultants to first define and then systematically structure several hundred metrics, henceforth referred to synaptic performance indicators SPIs.

These are collected at the plant operations, engineering, and top management levels in process industry operations, based on deep knowledge of how they affect plant performance. At the operations level, a typical midsized refinery has about SPIs, and a typical ethylene plant has about 77 SPIs. Approximately 60 percent of SPIs indirectly correspond to control variables, and 40 percent directly correspond to control variables. A midsized refinery will have about 93 high-level SPIs for daily viewing and use by management, SPIs for hourly viewing and use by engineering personnel, and SPIs for real-time viewing and use by shift operators Figure 1.

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Conceptual framework of how operations, engineering, and top management synaptic performance indicators SPIs are structured to align with high-level plant management objectives. These dashboards help control room operators analyze their operational performance and find areas for improvement, motivating them to achieve enhanced operation.

Plant control systems continuously receive a vast amount of data from sensors and devices, but the utilization of this big data collected in real time by the DCS has mainly been limited to front-line plant safety and line control. For this new methodology, in-house domain knowledge has been applied rigorously to first select the appropriate indicators impacting high-level management objectives, and then determining from where to collect the data to create the indicators.

For SPIs not measured due to a lack of sensors or analyzers, process simulation is implemented to calculate soft sensors for estimating unmeasured process variables from measured variables using rigorous process models. Process variables are optimized by setting an optimal range for each critical set point.

Analysis of historical data by process engineers and experts with extensive domain knowledge can determine the correct range for each set point, a complex task because many control loops interact with each other. Further complexity is added by also considering the effects of set points on the supply chain.

All this data can be combined to provide deep insight into the behavior of a process at any point in time. These SPIs data can also be used to trigger expert guidance in the form of messages when a variable goes outside of the ideal range, thereby supporting prompt action by even inexperienced operators Figure 2, right side.

By optimizing SPIs, operator actions mimic those of a multivariable controller, which is one of the categories of advanced process control, resulting in optimal control of related process variables. The dashboard tracks the performance of each control room operator during his or her shift by checking the uptime of an SPI time during which the SPI is in the ideal range or without alarm. Operators can check their performance with respect to the high-level objectives, and improvements can be visualized by comparing performance of operators across shifts. Example of performance dashboard for operations left side of diagram , and automated expert advice on specific indicators right side of diagram.

Plant engineering and third-party personnel can use this information for benchmarking, root-cause analysis or expert consulting for continuous improvement. SPIs and related dashboards can thus help engineers and operators transform their work from event-driven to profit-driven. The control room operator SPIs are used to inform the engineering team of possible improvement opportunities, creating aligned targets for the operations and engineering teams.

The engineering team can use structured SPIs and stored data for analysis of plant performance, for improvement opportunities and for analysis of other issues related to production. SPIs for management give a clear picture of high-level performance metrics such as facility operations, the difference between planned and actual production, and energy use. The balanced performance metrics associated with carefully-crafted SPIs lead to improvements in quality and efficiency, reduce inventory, ensure compliance and increase flexibility—ultimately leading to greater profitability.

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