Global Production Processes with Plant Granularity

Most manufacturing facilities have an intensely complex set of applications to manage the information necessary to accomplish production objectives. It is likely that this scenario includes many specific departmental applications ranging in age and technologies. What we want is operational harmony but what we see are dozens of disparate data sources and applications.  Trying to get a three year old Manufacturing Execution System (MES) to exchange data with an older warehouse system in a multi-plant enterprise is about as easy as getting Cuneiform tablets to exchange information with the Mayan Calendar. The example may be a bit extreme, but the efforts to support business activities through typical integration efforts has never been easy. In most cases, it falls far short of the desired result and can soon be outdated when the business requirement changes.

A New Approach

There is a better way – think process instead of application. In a recent paper I co-authored, Improving Manufacturing Excellence: Managing Production Processes across the Value Chain, a new information and process management approach was introduced. We call it Production Process Management (PPM), which is a process centric framework (not a technology) based on Business Process Management (BPM) tools and concepts. This is a totally new way to deploy and maintain enterprise or individual plant production processes quickly and incrementally, either on a plant-by-plant or multi-plant basis. This methodology provides the framework to establish and continuously improve production/operations processes with greater granularity while also enabling global process standardization.

Let me explain. Above is an illustration of a process to manage the collection of scrap data by shift, measured as a percent of finished product. An instance of this process is executed at the end of every shift for each product line, which is then reported to the corporate Enterprise Resource Planning (ERP) system, as a percent of finished product produced by shift.  In this case the scrap data collection process is identical across all applicable facilities while recognizing the specific data element may be retrieved from different physical sources at the plant (granular) level. In the example the granular aspect allows Plant A to use a PLC to maintain the scrap weight whereas Plant B may use a computer and plant C might use a manual data entry.

Global processes can come in nearly any form to fit how you want to run your business. It is easy to build into a process the variables that are then managed through process modeling, process execution and business rules. Another example is to confirm the qualifications of a worker at a production station before they are permitted to perform a task. The process might follow in this order: a) review the task, b) review the operator name and validate based on their login credentials, c) retrieve skill information for that operator to confirm their skills are within compliance guidelines, and d) continue to guide to the next required operation or take alternate action. The global process can be defined to work across the enterprise while still being able to accept a range of rules and variables from designated local information sources.

This process methodology can be summarized as follows:

  1. Model the process
  2. Identify data elements and sources
  3. Simulate the process
  4. Revise as necessary, and
  5. Deploy (execute) the process

By following this Production Process Management framework, it is possible to take a more holistic perspective across your operations. One of the results is better standardization of your business processes. Why should you care? Greater standardization will result in fewer challenges with monitoring and measuring performance improvement. Support and training costs will decline. And, best yet, a process improvement benefit can now be applied to multiple locations. This means that a Lean Multiplier effect is now possible whereby performance improvement benefits can be amplified to generate reduced waste on a much wider scale. Executing global processes with greater consistency will not only provide improved performance, but will provide more clarity on what processes are performing best, moving you a significant step forward on the road towards operational harmony.