Conventional wisdom says that you need to meet production targets, measured against throughput KPIs, to make customers happy. But – do your customers really want nothing more than fast, reliable production?
For most of the manufacturers we talk to, business is not that simple anymore. Customers are more demanding than ever, and their customers in turn are looking for more. They expect to see more value than just reliable, good products. They want to have their needs met in a timely manner, with fast, reliable communications from their vendor, wrapped in a productive, compelling experience.
Customers look for more value in business relationships
The more customers spend and the more complex the items are that they purchase, the more interested they are in innovation: more powerful products with enhanced capabilities that help them become more competitive and productive. What’s more, they are demanding top-quality maintenance and support services that boost the value of their spending.
How do you thrive through all these developments while handling the change management that’s also needed so you can optimize your processes, develop and launch new products, or realize new business models?
Finding the right context for OEE assessments and throughput KPIs
For a manufacturer, it always comes back to production. That’s the foundation of your business that everything else builds on. You need to know how you can adjust your throughput and production performance so you can make and deliver the products customers want, at the quality they value, delivered when they need them.
If you are tracking Overall Equipment Effectiveness (OEE), you are already using machine data to improve your operation. OEE is seen to be a reliable indicator of how well your machines perform, but how does it relate to your customer commitments and your throughput KPIs? When you look at your production data in light of the agreements between you and your customers, it may turn out that you need to increase throughput or risk falling behind.
That means OEE is not an absolute value. Neither are your machines simply productive assets that you turn on and run. You need to think of OEE and your equipment in the specific context of what you produce, for which customers. That may mean adjusting OEE targets depending on what’s being manufactured and increasing the throughput to meet customer expectations and throughput KPIs.
How well will your machines withstand increased workloads, and how do you have to adjust your predictive maintenance practices to avoid a breakdown? Real-time machine condition monitoring would highlight the risks and help your maintenance team revise their schedule for servicing machines. Some manufacturers find that it can actually pay off to manage machinery for shorter and more intense lifecycles but achieve greater throughput performance.
Relying on real-time data to gain greater agility
You face a similar scenario when you need to make adjustments in your production lines to make products of different specs for certain customers, or even when something as minor as the packaging is updated. Your OEE context and your throughput KPIs will be different, depending on your schedule and customer commitment. At the same time, the quality component of OEE may also have to change.
When you have the data to show you how your machines perform under such changed circumstances and what production adjustments are possible, you have a handle on the heart of your production operation. Then you can reliably adjust your upstream and downstream processes, planning, and forecasting to align with your new quality targets and throughput KPIs.
Blueprint for customer retention
Once you establish a working model for using OEE and condition monitoring to adjust your production and give customers the quality, timely delivery, or innovation they want, it becomes easier to respond to competitive challenges and ensure customer satisfaction.
When customers are interested in more powerful support and want to see more tangible value from the relationship with your company, you can combine current production data with equipment histories and engineering records to get creative. Data evidence will help you design and launch maintenance or collaborative engineering services and make them profitable.
Improve manufacturing outcomes with machine production monitoring