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BIRLA COPPER (Hindalco group) |
| Business Segment |
| The largest Indian custom copper smelter. |
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| About the Client |
| Birla Copper, is one of the leading member of India’s 2nd largest business house ‘The Aditya Birla Group’. It has set up a mega Greenfield copper Smelting and Refining complex at Dahej in Bharuch district of Gujarat, INDIA. The plant involving an investment of about $500 million is the largest of its kind in India. The plant produces world class Copper Cathodes, Continuous Cast Copper Rods & Precious Metals. The plant has its own Power Plant, Jetty and Water System to meet its infrastructure requirement |
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| Problem Areas |
| Birla copper receives the raw materials (Copper) by ship at its own jetty. The weighing system was connected to the DCS instead of PC, hence were incapacitated to adhere to the regulations of weighing, data indication or monitoring at the place of unloading. Its capacity is 150,000 TPA of refined copper and holds a market share of 40%. With this mammoth operations it faced some operational problems like |
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Use of DCS for recording the weights i.e. remote monitoring |
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Huge data loss in capturing the weights |
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Sizable difference in weights of billed and unloaded quantity of raw material. |
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Low accuracy levels |
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Above all, because of the above it was not able to adhere to the statutory regulations of weighing, data indication or monitoring at one place. |
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| Vision for the desired solution |
| The proposed solution was to streamline the acknowledgement raw material receipts as per the regulations and eliminate the discrepancies in weights. |
| How Indus solved/addressed the problem areas |
| A software solution was developed to capture the data from the weighing machine of Mettler Toledo make (Jaguar model), so that the system is capable of reading the data without loss and also generate pictorial flow of the process. |
| Results |
| Following the successful implementation of the application the organization benefited by |
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Facilitated to adhering to regulations more effectively |
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Eliminated the discrepancy in weights: billed and unloaded quantity |
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Increased the efficiency by reducing weighing time from 1min to 30 sec per batch (Avg. wt 24MT per batch) |
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Timely payment to suppliers: leading to effective vendor management |
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Eliminated human operations of the weighing machine. |
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