Issue link: https://iconnect007.uberflip.com/i/1534953
that see this as a strategic project under- stand the value. They come back and say things like, "I cannot even think how my life was before the MES." It's tangible. The key is the journey. You have a road- map and you commit to the journey; it's incremental. What is the primary factor in making the decision to start this journey? First, there needs to be a certain level of understanding of where I am as an orga- nization, whether I have adequate visibil- ity of my processes, and if they are under control and not depending on person A or B, or even machine A or machine B. Sec- ond, do I know how efficient my process is from a quality perspective and from a reg- ulatory compliance perspective if that is applicable? An interesting "soft" symptom of where you are with this is how much paper is needed in your shop for people to communicate. Do I need to call people? Do I need to send a memo from my supervi- sor to the other side of the factory if I need to change something? Those are typical pain points that we assess in the discov- ery phase. We help our customers by iden- tifying them and presenting a solution that can get rid of those pain points. It's always a process to understand where I am and where I could be with MES in my factory. You described pain points. When we feel a lot of pain, that's when change hap- pens. How bad does the pain have to be? Part of the ROI is to remove pain points by optimizing, which leads to higher yields, I would think. Exactly. Yield, throughput, cycle time, and OEE are typical key performance indica- tors we must understand if they're being measured and monitored adequately. Unfortunately, it's not always the case. We also need to understand whether we will install a system that will control the operations from a quality perspec- tive. Those things are indirect, related to the yield factor because I would be able to detect failures much earlier than prior to the MES, and we may have predictabil- ity or a much faster reaction time than if we would only analyze them at the end of the shift or when somebody discovers that this machine is producing bad parts and so on. Adequate degrees of automation will even stop the machine. We have this type of thing in highly automated facilities. So, MES directly contributes to a shop's typical KPIs such as throughput and quality. And bottom line dollars. Exactly. Having an intelligent system that can cap- ture and contextualize the information is paramount here because it's not enough only to have equipment or process data. Putting it in context is the science behind it. With this contextualization of data, we'll be able to detect those types of things and bring impact to the process. We'll know that historically there's a high probabil- ity that if you don't modify the tempera- ture, or if you don't modify parameter A or parameter B, you may have a higher per- centage of failures later on. Can MES be predictive on equipment maintenance as well?