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Manufacturers are swimming—some say drowning—in data. There are multiple types of production equipment and processes, each with its own proprietary database. There are thousands of data points contained in data silos, data in itself isn't the problem. What keeps manufacturers up at night is how to integrate, analyze, understand and act it.
Recently, Dr. Lloyd Colegrove, Director of Fundamental Problem Solving, Dow Chemical, joined us for a web-based discussion, “Maximizing the Value of Process Data – How Dow Implemented EMI”. During our conversation he outlined the three evolutionary steps he observed as Dow developed more sophistication using process based analytics:
Manufacturing is a long-term play. Systems are targeted not for the day or week, but rather for years or decades. Therefore, system development and improvement programs are long-lived as well.
What are the secrets of sustainable system improvement?
Mark Gavoor in his recent webinar The Right Data at the Right Place at the Right Time defined sustainable system improvement as:
Sustainable Improvement = Metrics + Lean + Process
The big promise of Enterprise Manufacturing Intelligence (EMI) is that it will transform your company into a high-performance, knowledge-driven organization. And, when that happens, you will be more productive and profitable.
Our common industrial temptation is to focus on the “easy” engineering part of management systems while deferring the more difficult people part of incorporating the system into the daily work life. However, we need to give organization and workforce issues the same attention if we are to develop successful and sustainable manufacturing management systems.
Industry analysts and the marketplace alike tell us that for a manufacturing company to prosper, it must incorporate Enterprise Manufacturing Intelligence (EMI) into its management practices. As Pierfrancesco Manenti of IDC Manufacturing Insights says, “The basic productivity gains in manufacturing have been realized. The next level must be achieved through Manufacturing Intelligence.”
It’s the too common plant management problem: too much data too poorly defined and improperly collected to be usable for process management and continuous improvement.
Automation and manufacturing system expert Charlie Gifford took on these issues in our recent webinar, “Designing Data Collection for Consistency that Improves Process Management”. One conclusion: since no quality system can be better than the data entering the system, management needs to step back, look at the process and determine:
World class manufacturing requires a complete understanding of what is happening in all parts of the enterprise. This means well organized accessible data that can feed analytics to provide effective manufacturing and management decision support., However, most companies maintain their process and business data in a collection of different databases that were built at different times for different purposes that were never designed to work together.
The Smart Manufacturing Leadership Coalition (SMLC) developed the recently released report “The Implementing 21stCentury Smart Manufacturing” to establish a roadmap and set priorities for modernizing US manufacturing with digital information and automation technology. The report discusses the needs for 21stcentury automation, data acquisition, management, analytics and reporting.