Data, particularly machine data, is a foundational component of every smart factory or OEE initiative. It fuels analytics, triggers actions ahead of problems or shutdowns, and provides insight for continuous improvement. Many companies start the smart factory journey with an automated OEE system because it’s a natural progression with a set of metrics they’re already familiar with. Despite advances in automated data collection and production analytics, a lot of manufacturing executives are still at odds about exactly which machine data is required to calculate OEE. Unfortunately, a lot of projects get sidetracked early on as stakeholders try to utilize every piece of machine-generated data from the multitude available. A more pragmatic approach is to apply machine data based on priorities around business goals. To that end, capturing the machine data required for OEE is a critical early activity for most smart factory initiatives.
- November 10, 2020 / by Kim Burndred
If your manufacturing business has ever survived a crisis — supply chain disruption, market demand fluctuation, distribution problems, or perhaps even a natural or economic catastrophe — it had an uncommon opportunity to shine through the adversity. More importantly it gives you a chance to learn from the outcomes generated by the organization’s responses to the disaster. We don’t know any that are eager to flush it all away — not just the performance gains, but the opportunity to do even more with the unexpected wisdom.
- July 29, 2020 / by Sean Lashmar
Recently, the Toward Zero team examined some effects of organization culture on manufacturing execution system (MES) decisions. In response to our article, “MES Tug of War: The Battle Continues,” Farukh Naqvi succinctly lays out ISA’s ongoing work to develop a framework and methodology for “solving conflict among the three diverse stakeholders” of an MES effort. While the ISA-95 framework delivers perspective on system integration and the thousands of actions and data points throughout a manufacturing enterprise, it also inadvertently reveals the need for enterprise-wide cross-functional collaboration.
- January 22, 2020 / by Doug Granitz
An overwhelming number of manufacturing execution system (MES) deployments fall short of the finish line; in their wake, they leave partially implemented and, therefore, ineffective solutions. A typical outcome: stalled digital transformation and a budgetary freeze for additional IIoT projects. It’s not an uncommon scenario for MES projects, yet most manufacturing companies seem unaware that many MES deployments fail to hit expectations.
- January 6, 2020 / by Kim Burndred
We see it constantly: “corporate” insists on one brand of MES, while the manufacturing plant wants something different. The execs running the show regionally or globally don’t trust plant management’s choice, while the plant believes corporate’s pick won’t work for them ― because “their situation and production environment is different.” This kind of battle isn’t limited to one or just a few industrial sectors ― indeed, automotive manufacturers, life sciences companies, food and beverage manufacturers, and consumer products manufacturers (also known as CPG companies) around the world have all seen and are at risk when the “MES tug of war” ensues.
- December 17, 2019 / by Diane Murray
Over the past several years, many large manufacturing companies, at some level, have invested in a digital manufacturing initiative. With a typical budget of $500K to $5M, these projects range from a strategy for smart manufacturing to implementing a manufacturing execution system (MES). Successful MES projects have delivered significant value and ROI. When considering a smart manufacturing project today, it's important to know what designs have proven effective and more importantly, what hasn't worked.
- January 18, 2019 / by Catalyst Team