Manufacturing Use Cases: Process Optimisation
Advanced analytics detect each step of inefficiency of operations which is measured by overall equipment effectiveness (OEE), analytics software can improve three components of OEE;
Uptime: ensuring machines are running especially in complicated systems
Throughout & Performance: Maximizing throughput by preventing slowdowns that are not visible to conventional analysis
Quality: Scrap and low quality cost the manufacturer directly
Analytical insights that help to predict and prevent machine malfunction, machine learning algorithms analyses historical data to determine which indicators signal the malfunction so that these events can be predicted.
This requires collecting historical data from legacy machineries which is difficult for companies to do. Industrial Internet of Things (IIoT) solutions solve that challenge by combining machine to machine communications. IIoT brings industrial devises connected by communication technologies that results in the systems that can monitor, collect, exchange and deliver valuable insights.
Benefits of Manufacturing Analytics
Improving quality assurance have direct impact on the revenue streams, in addition to the quality, diminishing capacity constraints on the factory floor through data insights enable business to fulfill exceeding demand requests.
Decreasing inefficiency in every step of operations have accumulated impact on the cost reduction, potential cost benefits of manufacturing analytics software;
- Reduce maintenance costs by 40%,
- Reduce downtime by 50%
- Reduce equipment capital investment by 3-5%
- Reduce worker injuries by 10-25%, saving companies $225M collectively
- Reduce energy use by 10-20%
- Improve labor efficiency by 10-25%
What are the Challenges?
There are technical and organizational challenges ahead to implement successful manufacturing analytics software. First challenge comes with organizational; many production facilities have conservative mindset and have inertia to involve innovative tools for improvement through IT software systems. Second challenge is domain expertise; as all processes have unique set ups, one size fits all approach does not work. New vendors mush have a domain expertise and have a deep understanding of complicated processes of their clients. So considering the right vendor which has a domain expertise and involving right stakeholders and aligning them all for the manufacturing analytics benefits for the business is crucial.
What is Manufacturing Analytics?
Manufacturers collect everyday data from operational data, built in sensors, historian software, ERP systems and spreadsheets. However more than 90% of the collected data is thrown away.
Manufacturing analytics is about getting all the data from different variety of sources and using it for increase operational efficiencies and preventing slowdowns.
Manufacturing analytics is focused on collecting and analyzing data rather than process control, it helps to monitor operational equipment effectiveness of the facility and creates action-oriented dashboards to visualize the performance.
Primary manufacturing analytics used cases today are process optimization and predictive maintenance.