The Connected Factory Global Smart Manufacturing Roadmapping Process has three phases:
- Assessment and Benchmarking
- Requirements Analysis
- Roadmapping and Implementation
Each of these phases includes multiple elements. This post focuses on the first activity in the Assessment and Benchmarking Phase which is an OEE (Overall Equipment Effectiveness) Assessment, a snapshot of the six OEE Job Loss Buckets addressed during the assessment is on the right.
OEE is a common productivity KPI (Key Performance Indicator) measured and tracked by many large and small manufacturers. OEE can be measured at many levels such as the machine operation level and the work cell level or on the production line and even factory wide. It is a useful KPI whether the manufacturer is a machine shop, injection molder, metal fabricator, assembler or has a combination of these capabilities. OEE is a composite metric which is calculated as the product of these three submetrics:
See this prior post for additional information about how to calculate OEE, and its factory floor application.
While many manufacturers intuitively know they have an OEE problem across the plant, we need to drill deeper to fully address it.
A key aspect of the Connected Factory Global Smart Manufacturing Roadmapping OEE Assessment is to define:
(1) Pain point(s) across the factory floor and (2) the OEE “Job Loss Bucket”. This approach can identify a pain point as granular as “Small Stops on Machining Cell #4.” Without setting this boundary during the assessment activity, it will be almost impossible to conduct a requirements analysis or produce solution roadmapping to improve OEE.
I have talked to many manufacturers who say they are quite familiar with OEE, believe in it and practice the measurement and management of OEE on their factory floor. However, when I conduct factory floor walk-thoughs, I rarely see OEE as a visible KPI on performance dashboards.
The causes of this paradox, I believe, lie in the fact that while OEE is empirically simple to calculate and understand, it is not so easy to collect, communicate and aggregate the data components needed for the calculation.
If the underlying data for an OEE calculation is perceived as old and/or untrustworthy by the team members held accountable for it, then the confidence in using it to assess the current status, make decisions or solve problems breaks down quickly.
There are three critical success factors relative to the successful implementation of OEE on the factory floor:
- Select a single pain point as a place to start.
- Isolate the “job loss bucket” to focus on.
- Leverage technology for data collection, communication and aggregation where possible.
Connected Factory Global’s Decision Driven® Solution Engine maps patterns of typical requirements and constraints with solutions which can accelerate your Smart Manufacturing Roadmap for OEE improvement.