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Curbing production wastage

Motherson Sumi Systems, a manufacturer of wiring harnesses for the automotive industry, was finding difficulty in handling the end-to-end production life-cycle process. the company was experiencing extensive wastage of raw material and delay in order delivery. In order to overcome these problems, the company went in for automation that helped in increasing productivity and RoI

Though the company had in place a cutting & crimping (C&C) machine that looked after various processes like wire cutting, wire stripping, and seal insertion, it needed to set up another C&C machine for jobs based on various parameters such as wire length to be cut, size of the terminal and crimping force. Hence, the company was looking for a solution that would not only automate the ‘machine set-up’ process, but also bring accuracy, efficiency and profitability.

Identifying the problem

Because the cutting and crimping of wires has to be done in large numbers and the C&C machine was the only machine to perform all the critical tasks, it was prone to errors that led to extensive wastage of raw material and delayed order fulfilment.

“This need was ITtaken up as a process improvement drive by the IT team in February 2005. It was realised that by simply automating these areas, the process could be made mistake-proof, and the machine set-up time could be reduced thereby saving in material wastage and enabling increase in productivity,” says Vandana Avantsa, CIO, Motherson Sumi Systems.

“While analysing the process for probable automation, it was found that there was a lot of manual calculations and data entry of the set-up data for the C&C machine. This made the process error-prone leading to extensive wastage of raw material (copper wire, terminals, etc) and delayed order fulfilment,” adds Avantsa.

Making the right choice

After identifying the real pain areas, Motherson thought of automating the machine set-up process. It chose the Shop Floor Control System (SFCS) for the same. The SFCS envisages automation of the ‘machine set-up process, aligning of the processes to increase productivity, mistake-proofing of wrong raw material usage and raw material batch traceability.

Technologies deployed were Bluetooth bar code scanners, adjustable sensors, controller, voltage regulators, bar code technology for utility and .NET base application for Daily Work Report.

The main challenge faced was the integration of software solution with C&C machines and user training and availability of production machines for the final testing. “Moreover, at the time of integration testing, there was a need to have the production process available to the IT team, which was critical. To meet these challenges we did the testing job only during off-production hours (lunch breaks, shift changes, etc),” she adds.

The unique factor

With the scan of a bar code on the instruction sheet at the cutting & crimping machine, set-up data gets automatically populated from the ERP upstream modules. Actual observations are directly transferred from equipment such as the micrometer and push-pull tester in the application. The company claims that data received is 100 percent accurate as there is no manual intervention.

In addition the solution provides machine life data for planning and scheduling preventive maintenance. Alerts related to the C&C machine maintenance parameters are sent by the system to the maintenance department through e-mails.

Unlimited benefits

With an investment of Rs 10.21 lakh and ongoing cost of Rs 3 lakh per year, Motherson achieved a good RoI and savings after the project implementation. The company’s return on investment is 620 percent and savings per machine work out to Rs 1.58 lakh. Overall savings with respect to 40 machines is Rs 63.34 lakh and over the next three years the company is confident that the initiative will reduce costs by Rs 2.5 crore. Expense reduction as a percentage of revenue is 0.0624 percent.

Road ahead

With the present solution deployed, the company is planning to create a dashboard atop this application to assist supervisors, plant heads and top management in decision-making. The design phase is underway and go-live is slated for December 2006.