July/ August 2013
Software to support next-generation people-centric manufacturing
Making sure employees are fully equipped to take productivity higher and off the charts
- Research indicates companies using manufacturing execution systems (MES) or manufacturing operations management (MOM) can provide less classroom training for operators.
- As the younger generation enters the manufacturing workforce, having modern systems is more critical than ever. These workers expect comprehensive information that is easy to use and always available.
- Today companies can use better production data to make better decisions more confidently and faster to improve profits.
By Julie Fraser
Are you ready for people-centric manufacturing? If this question sounds crazy, realize that other industry analysts are thinking this way too.
These analysts are not stuck in 1960s manufacturing; people-centric manufacturing does not mean labor-intensive manufacturing. There are fewer people doing more production work every day. Yet, leaders are focusing on their employees, making sure they are fully equipped to take productivity higher and off the charts.
Yes, this requires automation and instrumentation. It also requires lots of information technology (IT). As automation and IT become well established, people will be more critical than ever. The ability of people to make decisions quickly and take appropriate action is going to be the differentiator between leaders and laggards in production and manufacturing companies.
Why people are central today
People are the critical factor in manufacturers' success. Why? Because of the core business strategies many companies are undertaking-and the way the world works today. These examples show that today's automation and IT systems can only provide platforms from which people must make decisions and act.
- New business models seek to increase value to customers by adding services and complementary products. So the offerings are no longer just static products, but are based on an ongoing dialogue. In the end, determining what customers actually want and need is a discovery process. That means constantly changing products, triggering a need to improve how they are made.
- Many companies now come together to offer what customers need, whether in outsourcing, distribution, or other value-adding relationships. While each company's IT system may be good, people must collaborate across companies for all the parties to end up with a good outcome. The capabilities of each partner may also change regularly, changing the terms of these conversations.
- Many products are now sold around the world, with totally different market conditions, customer expectations, packaging, pricing, and regulatory needs. As emerging economies grow, these factors change-and likewise as conditions change in more established economies. Each product sold in each region becomes a vast matrix of special considerations that changes regularly. This growing slate of specific configurations is another factor that changes product mix, optimization, and best practices in the plants.
These situations cannot be handled automatically with process controls, instrumentation, and IT-no matter how sophisticated. People must step in and make decisions. As these types of trends accelerate in leading companies, people are once again central to sustaining leadership positions as manufacturers.
Turns out, the research minds at IDC Manufacturing Insights agree. IDC Manufacturing Insights enumerates three levels of the "factory of the future."
- The lowest level is the automation-intensive factory of the future, which is where manufacturers in developing countries focus.
- The middle level is the IT-intensive factory of the future, where producers in developed countries focus.
- The top level is the people-intensive factory of the future, where the leading 18 percent of manufacturers focus. This is not the same as labor-intensive manufacturing, but more suggestive of quick-decision and response-intensive manufacturing.
Automating can add productivity, but typically it is not sufficient except in standard, lower-margin production industries that are relatively static. Factories in the developed world have become much more IT intensive, with more and more software running on standard IT platforms. Yet, many of these production plants still struggle to drive improvements and be as flexible as needed in the unprecedented situations they face.
The skills dilemma
Figure 1. Most companies are increasingly concerned about employee skills.
The very sound of people-centric factories may sound scary for companies not confident in their plant personnel. The author's research with Manufacturing Enterprise Solutions Association (MESA) International shows that most manufacturers are more concerned than ever about the skills of their plant employees-both operators and supervisors (figure 1).
In 2011, the National Association of Manufacturers reported that as many as 600,000 manufacturing jobs remained vacant in the U.S. due to shortages of skilled workers. Other developed economies face the same issues. So how does this skills shortage square with the need for people to make sound decisions? Fortunately, the people-centric model rests on automated plants that are also using sound IT. So increasingly, less-skilled people can get up to a certain skill level and then learn on the job from their peers and the software they use.
Many years ago, research indicated that companies using manufacturing execution systems (MES) or manufacturing operations management (MOM) can provide less classroom training for operators and have better business results. That is because MES/MOM guides people through the operation-it is the control system for the people. It provides operators and supervisors a view of what is happening across the plant and what to do next, including a job list and detailed work instructions for each task if desired. It also guides them through the process of logging information required for quality problems and exceptions, regulatory compliance, or product track and trace.
This is great because the older workers who might have known how to make a plant hum are at or nearing retirement. In January 2013, a blog in Bloomberg Businessweek by the Boston Consulting Group's Harold L. Sirkin stated, "The average age of a highly skilled U.S. manufacturing worker is 56. Now is the time to train the next generation." We all know that these young people are wedded to social networks and mobile devices and expect everything to be delivered 24x7 via the cloud. Fortunately, the new generation of enterprise manufacturing software can do that, too. Most of the major MES/MOM offerings now have a mobile version and are available in a hosted cloud version.
MES/MOM has been supporting people in taking correct action for the 20 plus years the author has been studying it. It currently can also support employees in using the data from plants to make good decisions quickly and efficiently. This is primarily a matter of another new technology: big data analytics. In the plant-floor IT world, this functionality is commonly called manufacturing intelligence (MI). MI can be either independent but integrated to MES/MOM and other manufacturing applications, or an integrated module of the MES/MOM software.
Manufacturing intelligence for decision support
What is MI? It is a specialized version of business intelligence (BI) that is particularly designed to handle the formats, speed, and mission-critical nature of plant-floor data. Figure 2 illustrates (upper right) where MI fits in the total set of manufacturing applications. MI may also be called operational performance management, enterprise manufacturing intelligence, or plant dashboards. Over the past handful of years, MI has been one of the best-selling applications in manufacturing. And for good reason-the people who are using MI report better ability to improve production and business results.
Figure 2. Manufacturing intelligence is the production equivalent of business intelligence.
Why can the MI users make improvements more easily? Because they have a better foundation from which to make sound decisions.
Like BI, MI provides data aggregation, contextualization, analysis, correlation, visualization, and propagation to those who need to make decisions. Unlike BI, the time frames in which it operates tend to be minutes and hours, pulling in real-time data from plant operations around the world. MI can handle both time-series data from a historian and relational data from other applications. It is intended for use by operators, planners, supervisors, and managers in the plant facilities and the offices to see status across one or multiple plants, measure and even predict performance, and ensure that those vast oceans of plant data help improve business performance.
Because most companies have multiple systems in their facilities for quality, maintenance, calibration, scheduling, as well as overarching MES/MOM, MI is a critical application for data aggregation. Perhaps more importantly, MI can deliver useful views out to the people who run, supervise, plan, and manage the operation. Some companies even include predictive analytics with MI, delivering a forward-looking view that helps to optimize how the plants are running and foster better results in the future.
MI is still a relatively young application set, and it is sometimes implemented in immature ways. Figure 3 shows that most MI applications allow drilling down to help identify root causes of performance problems or of good performance. However, most do not roll up into enterprise scorecards to show financial impacts across all plants and are neither integrated into MES nor available on mobile devices. Leaders are starting to change that.
Figure 3. Many MI implementations deliver benefits, but are not taking full advantage of the integration and capabilities available.
Transforming people's decisions into profitable action
With any type of intelligence, the value is using it to take action to improve outcomes-both in production and for the financials. Because of the complex, fast-changing, and interacting set of factors in a production process and the sometimes shifting profitability of those operations and the products they create, this has always been a challenge. Today's manufacturing strategies compound that challenge. They tend to create high-mix, rapid-change, volatile environments where the value and profitability depends not only on the product itself, but on services and sometimes other companies.
Fortunately, the software is increasingly up to the challenge. In the early days of MES, you could get data in, but pulling it back out for analysis was challenging at best-and often considered impossible. Those with an older MES may feel they are covered, but that is not likely to be true. Those with a MES more than five or 10 years old are at a disadvantage. Fortunately, current versions of MES/MOM are designed to push data back out. Many include MI for comprehensive and rapid analysis, too.
A recent Gartner report based on research of companies using MES/MOM shows that not everyone is getting the benefits they expected. This is unfortunate, but clearly can be avoided. The report, Governance, Not Technology, Drives Measurable Business Value from MES, makes it clear that companies must do a better job understanding and building the business case, resourcing MES/MOM projects, and gaining buy in.
One of the best ways to do that, particularly in the face of the current skills shortage in the industry, is to provide education to the MES/MOM team. The MESA Global Education Program (GEP) is designed to provide IT, operations, and production teams with a foundation to go into projects asking the right questions, setting sound expectations, using globally agreed on terminology and standards, and setting up global centers of expertise that can support success over the long haul. It is incredible how much students learn-even those who have spent their careers studying this stuff. MESA manufacturer/producer membership fees act as 100 percent credit toward GEP, which is a great deal.
The bottom line is that companies using current MES/MOM and MI with good governance are making faster improvements than others. Figure 4 shows just two of those examples, where two-to-four-times the portion of companies was able to make significant 10 percent or more improvements in key metrics. The first is the operational metric "overall equipment effectiveness," a measure that combines the effect of quality, availability, and performance or speed. This aggregate measure can often help ensure the best outcome for the business. The business metric "manufacturing cost as a percentage of revenue" is a clear indicator of what room is available for profit and margins. If manufacturing costs are a lower percentage of revenue, then improvements are working not just in the plants, but for the shareholders.
Figure 4. Manufacturers with an operations dashboard are far more likely than others to improve on both operations and business performance metrics.
Today, companies not only can make better use of their production data, they can make better decisions, and they can more confidently take action that will improve their profits. However, this means not just more complex data and information. Today companies should have or begin planning systems for:
- automatically analyzing and displaying current results to operators and supervisors so they can make adjustments
- providing simple views of this intelligence, tailored to guide the few actions available to each individual or group making a decision
- showing predictive or trend-based data and not just history whenever possible
- delivering analytics to mobile devices for employees anywhere
- using always on cloud for 24x7 access for anyone around the world
- linking intelligence from MI to the action-oriented MES/MOM to drive rapid action
Most companies do not have systems for any of that today. Figure 5 shows just two of those factors, and that more of those with MI do some of these things. Those who can deliver this intelligence wherever it is needed gain a clear competitive advantage today.
Figure 5. Most companies do not make maximum use of their production data.
In the future, this will all be required to survive. As the manufacturing world gains systems that allow it to focus on data and information, the next step is to use that data and information for making sound decisions. Linking manufacturing to enterprise and financial systems through specialized MI and MES must be a foundation.
As the younger generation enters the manufacturing workforce, having modern systems is more critical than ever. Younger workers expect information support that is not only comprehensive, but easy to use, always available, and supportive when they need it. They will want to leverage the knowledge of more experienced workers around the world. Today you can provide them that.
More and more companies are rolling out MES/MOM and MI across their enterprises. Some are insisting on seeing similar data from their suppliers and partners as well. It only makes sense. People are making critical business decisions every moment of every day. The data is there for those to be good decisions, and now systems are increasingly centered on people too. Just in time for the new generation of workers to gain their skills and learn.
ABOUT THE AUTHOR
Julie Fraser (email@example.com or firstname.lastname@example.org) is principal of Iyno Advisors and is passionate about manufacturing using technology for better outcomes. She has researched manufacturing software and systems for more than 25 years, holding senior industry analyst positions at Cambashi, Industry Directions, and AMR Research, as well as writing the CIM Strategies newsletter at Cutter Information. She is also outreach director for MESA International.
Figures 1-5 source: Pursuit of Performance Excellence: Business Success through Effective Plant Operations Metrics © 2012 Cambashi Inc. and MESA International