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TEKsystems Global Services® helps clients implement an innovative Big Data for Manufacturing solution that provides a 360-degree view of shop floor performance, allowing for real-time corrective actions to improve efficiencies and reduce costs.
TEKsystems has worked with a diverse group of manufacturing clients across a wide variety of industries, including oil and gas, automobile, and consumer packaged goods, to implement our Big Data for Manufacturing solution.
The client, one of the world’s largest manufacturers, had multiple production lines in their plant, each producing a different appliance. Each line was made up of multiple machines that performed unique functions as part of the overall appliance assembly process. The machines were automated with various sensors to record performance data, such as temperature, speed and quality parameters. Even though data was collected by the machines, there was no single platform or view of the operational data displaying day-to-day enterprise data collected by enterprise resource planning systems. This meant that the day-end performance report only showed a high-level view of the shop floor’s performance and that it was only as strong as the weakest machine on the line, since individual machine performance and quality could not be viewed.
The client was looking for a way to better understand the operations and performance metrics for each unique machine and machine sensor so they could understand when and how individual machines were underperforming and pinpoint areas for improvement. Having a means to view more sophisticated operational analytics would allow plant managers to proactively tweak any performance issues on the floor as they occurred. It would also help plant managers identify patterns in equipment usage or equipment performance as they pertained to production speed, quality or errors. This increased insight would help improve overall production line performance, better ensure daily production goals were met, and provide a greater understanding for when and why new components needed to be ordered for an individual machine.
Below is a sampling of two additional client success stories.
Global medical device manufacturer
The client, a global medical device manufacturer, sought TEKsystems’ help in implementing Oracle MOC and OBIA Manufacturing Analytics so they could better understand and track when various medical devices were being manufactured and what specific components were going into each product, which would help ensure compliance with device standards. By implementing MOC and OBIA, the client realized increased insight into the various machines producing medical devices within their plants. The client also gained the ability to easily track and record relevant data for each machine on comprehensive dashboards.
Leading polymer and rubber manufacturer
The client, a leading multimaterial product developer, was using Oracle’s JD Edwards 9.0 to monitor and track internal machines producing rubber-based cushions. While useful for providing collaboration within the client’s network, the machines lacked a way to communicate with Oracle MOC 12.2.2, which would provide more comprehensive and in-depth reports of the various machines’ components and performance metrics. The client first partnered with two outside vendors that attempted to directly install MOC, but due to a lack of knowledge about the intricacies of integrating the two systems, both vendors were unable to deliver the Big Data solution the client sought. Aware of our success implementing our Big Data for Manufacturing solution at a number of other manufacturers, the client reached out to TEKsystems for assistance in getting their MOC solution up and running.
TEKsystems customized MOC to source data from JD Edwards software. The enhanced communication and customized Big Data solution allowed the client to view real-time BI reports on four separate reporting dashboards that showcase contextualized data collected from shop floor devices. This improved visibility established a greater understanding of production and individual machine metrics and performance, which has helped the client decrease machine downtime and improve overall operational efficiency.