Cutting-edge Predictive Analytics for HIROTEC Group
Hirotec needed to ensure continuous operations and to minimize unplanned downtime in its manufacturing facilities. Unplanned downtime is costly and compromises Hirotec's ability to deliver its goods to customers on time.
ThingWorx (PTC)The ThingWorx IoT Technology Platform. One Platform. Limitless Possibilities. ThingWorx is the only enterprise-ready technology platform that enables innovators to rapidly develop and deploy smart, connected solutions for the Internet of Things. Build Fast Connectivity and development tools made for IoT enable developers to quickly create, test and deploy solutions faster than ever thought possible. Build Smart Integrated capabilities of the platform enable developers to create more feature-rich solutions in a fraction of the time of other platforms. Build for Enterprises Developers quickly and easily create IoT solutions that are scalable, secure, and meet the needs of the largest of enterprises.
HIROTEC Group is a $1.6B Japanese corporation that is globally recognized as a premier automotive manufacturing equipment and parts supplier. With over 85 years of mass production experience and engineering discipline and 26 facilities in nine countries around the world, HIROTEC Group designs and builds roughly 7 million doors and 1.5 million exhaust systems a year, making it one of the largest private production companies in today’s global automotive market.
- CONNECTIVITY PROTOCOLS
Hirotec decided to partner with PTC and selected its Thingworx Technology Platform and KEPServerEX agent to rapidly develop and deploy IoT software and integrate it with its manufacturing systems. PTC with its IT capabilities proved to be an ideal partner to complement Hirotec's operations technology skillset.
HIROTEC also decided to use HPE Edgeline servers to support edge analytics. The ruggedized HPE Edgeline servers’ small footprint minimized the need for HIROTEC to sacrifice valuable factory floor space. In addition, the servers do not require specialized cooling to operate.
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- DATA COLLECTED
- SOLUTION TYPE
- SOLUTION MATURITY
Mature (technology has been on the market for > 5 years)
- OPERATIONAL IMPACT
Impact #1 [Management Effectiveness - Operation Transparency]
Through the Thingworx platform, HIROTEC gained real-time visibility into its business operations, which in turn allows the company to address issues that impact its efficiency and throughput.
The solution also enables HIROTEC to perform sophisticated analysis of historical data so that it can better understand production facility performance and ways to drive improvements.
Impact #2 [Efficiency Improvement - Production]
HIROTEC will be able to build on the solution to enable augmented reality applications to further advance its manufacturing capabilities and efficiencies — completing its transformation from smart factory to smart enterprise.
Impact #3 [Cost Reduction - Capital Investment]
The need to invest in new Computer Numerical Control (CNC) machine via analysis that supported improved efficiencies and elimination of process bottlenecks was eliminated.
- QUANTITATIVE BENEFIT
Benefit #1 There was a 100% reduction in time to manually inspect production systems, enabling technicians to re-invest that time in tasks that drive more value to production workflows.
- USE CASES
Predictive MaintenancePredictive maintenance is a technique that uses condition-monitoring sensors and machine learning or rules based algorithms to track the performance of equipment during normal operation and detect possible defects before they result in failure. Predictive maintenance enables the reduction of both schedule-based maintenance and unplanned reactive maintenance by triggering maintenance calls based on the actual status of the equipment. IoT relies on predictive maintenance sensors to capture information, make sense of it, and identify any areas that need attention. Some examples of using predictive maintenance and predictive maintenance sensors include vibration analysis, oil analysis, thermal imaging, and equipment observation. Visit our condition-based maintenance page to learn more about these methods.