by June 30, 2011 0 comments



With the increasing competitiveness, manufacturers need to focus on reducing their losses in operations and increasing their efficiencies so that profits may be increased. The difficulty of managing production shop floors and their productivity is vastly exaggerated due to the limitations of production machinery to directly plug and play into a real-time DSS. The sheer variety and diversity of such machines make it challenging to create an infrastructure that can scale across any type of machine. Such an infrastructure is required to connect the shop floor to the top floor, and drive real-time shop floor productivity as well as provide timely, fast-based inputs for strategic decision making. Sophisticated microcontroller based hardware for industrial shop floors, last mile networking, and sophisticated data acquisition and real-time analysis software have been developed to overcome this business problem, and has been successfully deployed under the name of TPM-Trak.

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The TPM-Trak is targeted at automating the data collection for productivity and O.E.E and presenting them after analyzing based on industry standard KPI methods. The real —time, data acquisition technology, techniques and process of TPM Trak eliminates manual entry of any production data and parameters, and facilitates accurate, fact based decision at the right time. It consists of hardware and software. Software is based on client-server architecture. Hardware, on the other hand, automates the acquisition of real-time domain-rich production data, cycle data, load/unload data, losses etc. Hardware is compatible with any CNC, PLC or conventional machine, any application like metal-forming or metal-cutting and with any manufacturer.



Targeted users

It is basically targeted at daily management tasks, where consumer is the production department. On the other hand, when it comes to scheduling, costing and planning, consumers are management, industrial engineering department and shop floor employees. Production managers, supervisors and top management are also benefiting from the project as they are now getting real time data to analyze the production.

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Challenges

Before the project was implemented, the main challenge that company faced was to connect the different nodes of data collection, for example; CNC machines, PLC machines, welding machines, etc. As a traditional manufacturing setup, where data collection used to happen manually in log book, acceptance for a new concept of collecting real time data was difficult. Apart from that the technical challenges that company faced was of managing data acquisition and analysis of real-time dense data, which had to have correlation at all time for BI purpose.

The Result

But they overcome these challenges and achieved the return of investment in just 60 working days.

After getting access to an accurate online data collection methodology for data collection and online OEE monitoring and with increased employment involvement and accountability, company is able to increase its productivity by 20%. There is also an increase in OEE by 20%. This automation also saved time in machine programming, which in turn reduced the setting time of machines.

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