Digital Twin Improves OEE Of Plant Machinery
HOW MANUFACTURING COMPANIES CAN IMPROVE OVERALL EQUIPMENT EFFECTIVENESS USING DIGITAL TWIN-IAPM
When you hear the phrase Overall Equipment Effectiveness (OEE), what are the three words that immediately flash in your mind?
Most of the time it's Availability, Performance & Quality. But have you wondered about other factors like equipment failure, equipment idling, reduced throughput, process defects, slow cycles, unplanned stoppage, quality rejection etc.?
William Edwards Deming once said, “without data, you are just another person with an opinion”.
Do you have relevant data with which you can decipher factors that drive fully productive time and valuable operating time for your assets?
If yes, you are on the right track which will help you to drive the business outcome for your organization through digital intervention. If not, Bosch & Microsoft can help you to evolve in this direction.
Bosch can build with you on Azure, Digital Twins for your assets that help you to drive integrated asset performance management. A Digital Twin can handle business challenges that are predictable and avoidable, which helps garner useful insights. Engineering insights can help improve efficiency, reduce unplanned downtime, reduce maintenance costs, and improve quality. Business insights can help understand asset criticality, plant efficiency, and reduce failure mitigation cost by enabling predictive maintenance.
For instance, a Digital Twin could help manufacturing companies employ field telemetry remotely to monitor hundreds of turbomachinery in the plant and their real-time electrical & mechanical fitness, speeds, energy consumption levels, fluid characteristics, kinematics & thermal aspects etc. This can help them prepare for breakdowns even before they occur not only at a particular machine but across the network. This gives you the visibility on cascading effects on upstream & downstream. This breaks organizational silos, drives cost efficiencies, and reduces uncertainties in business outcomes. Here the Digital Twin was helpful in two ways,
1st - A Digital Twin helped you to apply the theory of constraints.
2nd - It helped you transform data into information, information into knowledge, and knowledge into wisdom.
With this, you now have visibility on decisions and actions.
Now, you can drive Reliability Centered Maintenance & Total Productive Maintenance.
This precisely enables you to evolve and improve OEE.
A Digital Twin is a change agent that helps you drive meticulous Digital Transformation that can instill efficiency and help offset increased costs of infrastructure, materials, and components, with predictive and preemptive maintenance scheduling as well as agile production processes, causing less wastage. This would also help reduce production downtime and lead times, giving enterprises a competitive edge.
Bosch & Microsoft can help you build Digital Twins on Azure, enabling you to improve OEE through digital intervention. To do this you need to first prepare the data that you have from your manufacturing area. Bosch enables you to put in place equipment metadata, normal & abnormal operating conditions, failure history, repair history, maintenance history etc. These data sets will be consumed by the mathematics & physics-based models that would run on Azure which will have clear classification as static data & temporal data. The high-fidelity simulation models that run utilizing Azure HPC environment will help you derive predicted outcomes of multiple what-if scenarios based on which you could configure your machine operating conditions for the best possible OEE value for the given production cycle.
For more details please visit:
Bosch Digital Twin - IAPM
Microsoft Azure
Microsoft Azure Marketplace
Author
Joni Lehtonen ► Sr. Industry Executive – Manufacturing, Microsoft
Prahallad CR ► Partner Customer Solutions, Bosch
Bhuvan Shetty ► Sr.Manager Sales and Global Strategic Partnerships, Bosch