Since the advent of data walls and management dashboards, the relationship between the metrics used for decision-making and real-time and hierarchical data has become increasingly close. When investing in process improvement, do you have a sufficient understanding of Key Performance Indicators (KPIs) and Manufacturing Execution Systems (MES)? While process control continues to be highly sought after, production line optimization techniques are losing popularity. From the CEO down, everyone wants to benefit from process control. Through the demands surrounding video walls, information portals, and management dashboards, we see a desire to visualize the control processes that impact system performance. Competitive pressure among companies to achieve excellent basic operational levels, along with globalization, is focusing more on the factory, manufacturing plant, or shop floor. Whether control engineering can fully master this strategic role at a detailed research level is a significant challenge. The strategic significance of this role can be summarized in three letters: KPI. Key Performance Indicators are the metrics for judging success or achieving expected goals, and there are various opinions on how to measure them throughout the industry. Industry analysts, organizations, and companies are conducting in-depth research and analyzing how to define, create, calculate, and distribute KPIs. Control engineers need a thorough understanding of these concepts to effectively utilize KPIs. “Control engineers are no longer satisfied with simply looking at how straight the curves on control charts are to understand the performance of a controller,” says John Snodgrass, a control engineer at Chemtura, a specialty chemical company in Morgan City, West Virginia. “With today’s technology, in today’s market, professional operators are no longer ‘operators’ in the traditional sense. They are not just operators turning valves. And control engineers are no longer simply control personnel,” Snodgrass says. “They should look at the information available and try to figure out what they can do to make the product more efficient. If they don’t, they won’t be far from being eliminated by the market.” MESA International, a trade association focused on Manufacturing Execution Management (MES) systems, began actively researching KPIs early last year. In October 2006, based on its investigation, MESA published an initial report entitled "Metrics that Matter: Uncovering KPIs that Justify Operational Improvements." However, MESA explained that this was only a preliminary study of a complex project and was still superficial. Therefore, the MESA working group continued its in-depth research, particularly on the complex relationships between KPIs applied at different operational levels. One common channel is the plant management level, where a large amount of data is generated for multiple KPIs to access. Another common system is the MES platform, where data is aggregated and interacted before being transmitted to the upper-level headquarters system. Display boards and data walls present this execution process in an output format. [align=center] Behind the impressive data and network-connected display boards lies a matrix full of models, tables, and graphs. KPIs are the measures of whether goals can be achieved. [/align] Due to their importance to enterprise operations, KPIs and MES are gradually becoming an indispensable foundation for plant-level operations. In today's world, those who don't seriously consider their operating models are unlikely to achieve the business performance they could. "Everything control engineers do ultimately translates into monetary gains," says Jim Christian, product manager at Honeywell. "It's important to know how much profit your work brings to the company. Stable operation translates to more reliable performance, higher yields, better catalysis, and longer equipment life, which can also reduce the use of chemicals. All of these are quantifiable." Christian believes that one interpretation of KPIs for control engineers is "a metric for understanding how your work contributes to the company's profitability, so you can know if you've made the greatest contribution." There is a fairly widespread disconnect in most organizations regarding data filtering and data flow connections across different standards. "Many of our clients only see KPIs as tools for collecting data," says Claus Abildgren, manager of product marketing and development at Wonderware. "They don't understand that the key to business operations is identifying the useful data that can be used for decision-making." This disconnect exists in both top-down and bottom-up processes, as shown in the survey later in the MESA report. “What surprised us was that almost no one realized that every step from economic goals and metrics to the sales level is inseparable,” said Julie Fraser, head of the Industry Guidance Center, an industry consultant in the Boston area. Fraser has signed an agreement with MESA to participate in the “Metrics That Matter” industry survey report. “Only 3% of the companies we surveyed considered their connections to be tight. We didn’t expect that number to be large, but we didn’t expect it to be so small either.” Colin Masson, a research lab director at AMR Research Center, said that it’s possible to skip some data points and focus on one to build a set of metrics. The graph above shows the usage of different metrics as percentages. The reason for this problem is the weakness of downstream infrastructure technology; in other words, the inability to handle the massive amounts of data being used and generated. “AMR has partnered with several vendors whose management has over 5,000 solutions,” said Colin Masson, head of network operations supply at AMR Research Center in Boston. In this context, he said, "We can skip certain data points and focus on one to establish a set of metrics. Although this is only a stopgap measure compared to extracting useful information for upper management from millions of system data reads every day, it can still be effective in many situations." The Development of Data Models This massive data collection fundamentally caters to the growing need to establish widely usable standardized models for production data. Establishing widely usable production data models is to ensure that, after MES gained widespread attention, the model, as a core software function, becomes one of the market drivers; it is also why suppliers of real-time automatic control and human-machine interfaces invest in model-driven integration devices such as Rockwell's FactoryTalk, GE Fanuc's Proficy, and Invensys' Infusion platform. To quote Peter Martin, Vice President of Strategic Risk at Invensys, this is a "general-purpose computing environment." Many manufacturing companies are striving to unify the KPIs used by their production departments with the metrics followed by their management and executive departments. Many other factors contribute to the popularity of MES and KPIs, such as increasing product and process complexity and meeting corporate compliance requirements. Align Technology manufactures a production line that can create custom-designed orthodontic tools for individual clients. After receiving an order, the company's headquarters in Santa Clara, California, forwards it to its laboratory in Costa Rica. Clinical technicians create 3D models, which are then sent back to the responsible dentist for confirmation. Finally, all order information is transferred to the company's manufacturing division in Mexico for final processing. After adopting an Enterprise Resource Planning (ERP) system, Align Technology switched to MES to recover information lost from manual record-keeping. It uses Production Center MES, a component of the FactoryTalk platform developed by Rockwell Automation. “We produce 50,000 custom modules every day—and each day’s 50,000 is different,” said Michael Henry, CIO and VP of IT at Align Technology. “Initially, we used generic KPIs—cycle time and gross profit.” By gaining a clearer and more precise understanding of order logistics, MES helped solve problems such as excessively long cycle times and high costs. This real-time monitoring of order transfers across different regions helped Align Technology identify its bottlenecks and achieve seamless integration of the entire process from order receipt to product manufacturing and final finishing. “The production cycle, which used to be two weeks, is now reduced to just five days; and the gross profit margin, which used to be 58%, has now increased to 69-70%,” Henry said. What is the role of standardization? Common business standards, such as cycle time and gross profit, are relatively widely accepted; the development and promotion of production standards are much more difficult—unless your industry already has production standards to reference. Utica, ConMed Corp., located in New York, is a company that manufactures surgical supplies, medical stents, and other medical devices, and complies with Good Manufacturing Practices (GMP) outlined in 21 CFR Part 820 for medical device manufacturers. [align=center]“What surprised us most was that almost no one realized that every step from economic goals and metrics to the sales level is inseparable,” said Julie Fraser, head of the MESA industry report “Metrics That Matter.”[/align] “We’re in an industry with very strict regulations, which dictates the KPIs we have to follow in our operations. We have to first validate our process systems against the regulations to measure the necessary variable data so that once the indicators are set, just seeing these data tells me the system is running smoothly,” said Bill Wheatley, manager of manufacturing engineering at ConMed. “Then we start thinking: What is our first-pass yield? Can we continue at this output level? Are our preventative maintenance effective? Are we facing significant risks?” Wheatley says that implementing MES is key to ensuring the smooth and efficient operation of the entire process. ConMed uses the Visiprise MES system. How do companies determine which KPIs to use? Essentially, it's a top-down decision-making process. "Theoretically, you first understand the goals and strategies of the decision-making level, then establish the necessary execution standards for each department to achieve those goals, and then decide on more granular things in turn," says industry trend researcher Fraser. "You might even want to create a standard for the machine itself." Eliminating Boundaries From a holistic perspective, KPIs are very complex, and as a "science," they are still in their early stages and constantly evolving. But based on current progress, they remain closely related to the field of control engineering. Research in this field shows that everything is intrinsically linked. "For many years, people have traditionally divided automatic control, MES, and IT into three separate levels," says Martin. "But this is just an artificial classification." In the past, this was indeed necessary, he says, because due to the limitations of past technology, different problems could only be separated and handled according to the specific requirements of each level. With technological advancements, "this era of classification is over," says Martin. The driving forces of business operations enable KPIs to link decisions to retail. Therefore, KPIs have become a dedicated tool for business operations. This is what control engineers need to master and excel at. Forget those flashy data walls and connected dashboards; focus on the standards behind the data. Your company's future will depend more on your ability to transform data into intelligent decision-making.