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
Are manufacturers aware they have hidden production capacity? Companies that find and free up hidden production capacity can avoid costly equipment purchases, open the door for additional sales, or reduce the time and cost of existing production.
I’ve been a part of organizations that were struggling to satisfy customer demand — we simply could not produce enough product, or at least the right product at the right time. Determining how to resolve the issue would often put the operations engineering and production planning teams at odds. The solution most obvious to engineering was to continue running products in basically the same lot sizes, but at higher speeds. This approach required expensive new equipment. Besides the equipment purchase, there were other significant costs: inventory builds, downtime for installation, debug after installation, and operator training.
- August 28, 2020 / by Patricia Hatem
Manufacturers serious about improving OEE need to invest in automated data collection. Though the intention of manual data collection is good, this approach doesn’t provide real-time insight or the level of accuracy and detail that an automated data collection can produce. Perhaps more importantly, automated data collection helps you shift employees’ attention to high-value work like running machines and solving problems that hinder operational performance.
- August 6, 2020 / by Patricia Hatem
Manufacturing companies are still eager to use OEE. Some industry analysts say that it's “dead,” but not everyone in manufacturing agrees. Yes, it’s high-level, and as a standalone metric it’s not particularly actionable. However it’s also a powerful measurement that nearly anyone in a company can quickly digest and use as a starting point to uncover why things aren’t going the way they’re supposed to. That’s not to say that OEE hasn’t been the subject of significant debate — and even angst — since it first made an appearance in Seiichi Nakajima's 1982 book TPM Tenkai. (later published as Introduction to TPM: Total Productive Maintenance, also by Seiichi Nakajima).
- May 20, 2020 / by Diane Murray
- April 7, 2020 / by Patricia Hatem
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