How to Improve Overall Equipment Effectiveness (OEE): Practical Tips
Dan White
What is Overall Equipment Effectiveness (OEE), and what can it do for your operation? Many manufacturers understand OEE as a critical operational measurement, but few know how to properly assess OEE in a manner that stimulates continuous improvement. This blog identifies areas where OEE is often overlooked or mis-leveraged.
Overall Equipment Effectiveness (OEE)
The formula for capturing OEE is OEE= Availability x Performance x Quality. OEE unlike many productivity measurements, accounts for all losses (Time, Speed, and Quality) that occur during a production run. Most people associate OEE with documenting and increasing productivity, but OEE scores are subjective.
Manufacturers should consider OEE scores as dynamic assessments, continually identifying areas of improvement, rather than fixed, definitive measurements. Some highly successful manufacturing facilities can post OEE scores below 50% regularly. Success is in the eye of the beholder. When manufacturers within an industry compare their OEE figures, they often discover significant disparities. It's crucial to recognize that while OEE is an invaluable tool for evaluating and optimizing processes within a facility, it should be used judiciously when making comparisons across different sites, products, processes, and plants.
Facilities often factor various elements into their OEE scores. At the start-up, the primary goal is to minimize variations between shifts or product transitions. After addressing major efficiency concerns within a facility, chasing after the more minor losses often becomes a matter of combing through details to achieve incremental improvement.
However, OEE can and should always be used as a measurement to aid in productivity in multiple departments of a company.
Some additional areas where OEE is overlooked or mis-leveraged include:
SKU Price Adjustments
Forecasting and Scheduling
Maintenance Planning
SKU Price Adjustments
One of the universal truths of manufacturing is that it costs money to make products. Without accurate operational data, companies risk over or under-costing manufactured goods. In both over and under-costing scenarios, the company loses profitability. When products are under cost due to high efficiency, the company leaves valuable manufacturing time on the table. When production runs long due to systemic inefficiencies, the company’s variable product costs increase. Alternatively, some products average higher scrap/defect rates, and failure to account for additional waste can lead to a higher cost of quality. Accurately calculating manufacturing costs allows companies to plan for increased profitability.
Forecasting and Scheduling
“How many times has your facility run the same small production of the same product during the same week?”
For most facilities, the answer to that question is “too many times.” In general, shorter production runs lead to lower efficiencies. Setup, clean-up, and machinery adjustments all take time, and the effects of these inefficiencies are extrapolated during shorter production runs. In some instances, the manufacturing costs might run higher than the potential profits of the manufactured goods. Extending production runs allows facilities to eliminate the inefficiency related to non-value-added operations activities.
Accurate manufacturing data leads to accurate manufacturing forecasts. Accurate manufacturing forecasts lead to better resource allocation and reduced cost. For example, bottleneck management is one of the most important considerations for operations professionals. A healthy appreciation of bottlenecks will also inform how capital resources are allocated, improvement projects are determined, and headcount is calculated. Bottlenecks hold the key to increasing plant capacity and achieving a lower cost of production.
Through using highly accurate forecasts, industry-leading organizations refine the decision-making process surrounding inventories, employees, and CAPEX. Industry leaders know that many operational costs can be negated or decreased simply by aligning inventories, employees, and manufacturing hours.
Maintenance Planning
Can we predict when a machine’s maintenance regimen begins to impact productivity? Sometimes. Using decreases in machine efficiency to plan maintenance can pay serious dividends. But, without knowing when and why downtime occurs, it’s nearly impossible for companies to create and manage a proactive maintenance program. Validated real-time operational data provides insights into a production line’s overall health. Healthy Preventative Maintenance and Machine Diagnostics programs are both driven by accurate data.
How to Improve OEE In Your Manufacturing Facility
In most organizations, OEE is an underutilized metric outside of the operations group. However, OEE data can be leveraged to provide relevant data to most departments of a manufacturing organization. Data-driven decision-making is one of the hallmarks of virtually every industry-leading manufacturing company. Accurate data allows these organizations to circumvent anecdotal reasoning and concentrate on quantitative deductive reasoning.
Saves time: OEE downtime issues are addressed in real-time when issues arise; not hours, days, or weeks later when managers compile a manual report.
Improves productivity: Facilities can improve resource usage in several ways. Sensors can capture the data that operators and managers once laboriously collected manually. Decision-making is data-driven rather than based on ‘how things are always done.’
Controls costs: Because problems are solved in real-time, and the data drives the costing calculations, facilities will see a reduction in rework, scrap, and increased customer satisfaction by getting it right the first time.
So, is your organization ready to join the more than 2000 facilities that trust SafetyChain with their data? Learn about how SafetyChain addresses OEE and digitizes Production and Maintenance Management.
About the author: Dan White is a Continuous Improvement Coach at SafetyChain Software. He has over 20 years of experience in manufacturing, having worked across a diverse range of industries including dairy and breakfast foods to specialty chemicals. With a Master’s in Operations Management, Dan has demonstrated his expertise in various leadership roles spanning Operations, Maintenance, Continuous Improvement, and Sales.
