Ten reasons to build a process model for a manufacturing plant

A process model can be anything from a simple spreadsheet to a complex model that includes all aspects of a real-world manufacturing plant, which includes only what is necessary to answer vital questions.
By Philip Lyman, CRB April 2, 2018
The top 10 reasons why you should build a process model. Courtesy: CRBA process model can be anything from a simple spreadsheet to a complex model that includes all aspects of a real-world manufacturing plant. However, the best model does not include everything. It only includes what is necessary to answer questions.
There is an art to selecting the right subset of the real world to model. One question to consider: Under what circumstances is a model and simulation project likely to add the most value? Here are some situations we have encountered where modeling has provided valuable insights and led to reduced cost and/or increased throughput. 
1. Determine equipment number and sizing for a facility design. As an example, how many bioreactors and purification trains are needed to meet the 10-year forecasted demands?
2. Check for process bottlenecks. Most processes are very complicated—lots of equipment and resources. Sometimes, the bottleneck varies over time or as a function of process variability. Knowing where a bottleneck is and how constraining it is can help improve throughput.
3. Size a utility system. Manufacturing plants often have many utility demands, some of which may be poorly characterized. Factors such as sanitization schedules and preventive maintenance can affect the delivery of critical utilities. Without the availability of these utilities, when needed, the throughput and/or the product quality may be impacted. Some amount of overcapacity is typically built in during design. Rather than simply guessing a value, simulation allows for quantifying and fixing the level of over-design.
4. Optimize the layout. Alternative layouts can be quantitatively compared with a model so the best one in terms of operability and cost can be selected.
5. Determine staffing. When does it make sense to add another operator or another shift?
6. Optimize a laboratory. This may mean changing the layout, adding the right number of pieces of test equipment or streamlining operations.
7. Clean each piping segment. Cleaning in place could be a bottleneck in a complicated piping network.
8. Map material flow into a large facility. Raw materials must be moved from the warehouse for weighing and dispensing and then onto solution prep. If they are late, the buffer could be late, and the product batch may be impacted. Conversely, if materials are too early or the buffer prep scheduling is too conservative, extra inventory and associated costs could result.
9. Reduce costs. Understand all the elements of the cost structure. Where attention should be focused to reduce the cost? Is it focused on the easy way to change elements, or is it focused on the elements with the biggest impact.
10. Learn more about the process being modeled. During every simulation project, we (and our clients) have learned something new about the system being modeled. This insight often leads to unexpected improvements. As an example, one client was pleased to learn how to increase capacity by 25 percent without a costly capital project.
If any of these 10 items describes your manufacturing plant, consider process modeling and simulation as an efficient method of learning new ways to improve processes and operations. Models can be used to evaluate alternatives and justify the implementation of the most desirable options. Contact us to see how we can help.

Philip Lyman, director, process simulation, CRB, a CFE Media content partner. This article originally appeared on CRB’s website.