Operational Efficiency Through Data-Driven OEE
by Bill Rokos, CTO, Parsec Automation
As Industry 4.0 and smart manufacturing reshape the modern industrial landscape, automation is helping today’s manufacturers tackle new challenges and changes head-on. From geopolitically driven supply chain issues that necessitate having multiple (and contingent) suppliers to ongoing labor shortages that push teams to their limits, manufacturers are looking toward dynamic processes to tackle today’s greatest challenges.
Succeeding amid this volatile, hyper-competitive landscape requires precise, contextualized insights that optimize efficiency. This is where overall equipment effectiveness (OEE) comes into play. OEE (the combined product of availability, performance, and quality) is a way of quantifying the performance of manufacturing equipment and is used as a benchmark for performance comparison and tracking progress.
The Ins and Outs of OEE
OEE was developed in the late 1980s by Seiichi Nakajima, author and the father of total productive maintenance (TPM). It was intended to provide a measure by which manufacturers could benchmark machinery, industry standards, and production periods, highlighting production issues and profit losses to guide improvements.
Measured on a scale of 1–100, OEE evaluates where a piece of equipment sits on the scale of operating efficiency, with maximum efficiency/zero downtime yielding a perfect score (100) and not operating at all as the lowest possible result (1). The metric can help manufacturers across sectors pinpoint and resolve specific inefficiencies, helping, for example:
- Automotive manufacturers avoid the domino effects of downtime related to machine or cell outages.
- Food & beverage manufacturers monitor processes and improve adherence to stringent safety and reporting regulations.
- Consumer packaged goods manufacturers stand out in a crowded, rapidly changing market.
At its invention, OEE was calculated using data collected by non-real-time information systems and analyzed using structured data tables. Nearly 40 years and countless technological advancements later, manufacturers still use the equation to evaluate their most advanced machinery, now with all the benefits of Internet of Things (IoT) monitoring and real-time data collection. However, manufacturers only get those benefits if they have a sound data management plan to match.
Data Benefits, Strategies, and Challenges
OEE’s components—availability, performance, and quality—are, themselves, complex. Each is influenced by a variety of factors within a plant. But the most important of these underlying factors is shared between all three measures: data quality.
OEE is only valuable when the data informing it is accurate, accessible, and up to date. Of course, data management can be a complex beast, and manufacturers may experience some challenges as they get started.
Common data management issues (and their solutions) include:
- Data overload, or an imbalance between data capture and data processing. Sometimes facilities generate too much data for their system to parse and analyze, leading to inefficiency and data paralysis. Data cleaning can help manufacturers organize, standardize, and streamline their data so it becomes more manageable.
- Lack of real-time access hinders a facility’s overall efficiency and ability to iterate toward improvement. Smart sensors can help. They attach directly to facility equipment and, with the help of the IoT, feed real-time data directly to the processors, minimizing latency and maximizing actionability.
- Data inconsistency complicates and tangles manufacturing operations, making it much harder to monitor and improve performance. Implementing a central software hub like a manufacturing execution system (MES) will help manufacturers unlock a single source of truth—one that centralizes and contextualizes all facility data.
With a sound data management strategy and an awareness of common challenges, manufacturers can position themselves to take full advantage of OEE and all it has to offer. But even beyond the bounds of OEE and its components (availability, performance, and quality), manufacturers can use data to holistically optimize the areas of production that might not be captured in the equation.
The Work Ahead
To address today’s challenges, manufacturers must pursue every opportunity for incremental improvement. OEE will help them rise to the occasion. It’s your manufacturing operations report card: it’s a way of measuring how well your equipment is performing. In a world where every percentage point of efficiency can translate to thousands—or even hundreds of thousands—of dollars in savings, it’s a metric that cannot be ignored.
Understanding, accurately calculating, and acting on OEE can help manufacturers minimize waste, optimize team performance, meet demands, and improve efficiency—all key in the journey toward realizing and implementing Industry 4.0. But there’s much more to OEE than the score itself. It helps manufacturers manage productivity, cut costs, and streamline processes, so teams can move beyond mere data capture. It turns information into meaning that supports a more proactive, data-driven approach to operations.
