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Manipal Journal of Science and Technology

Abstract

The two major challenges that industries are facing today are continuous improvement in productivity and quality of the product. Bosch Production System (BPS) is one of the leading manufacturers in diesel system equipment. Fuel Injector is the main product of Bosch India Nashik. This plant produces around 10,000 injectors per day. They have a mass production and it may happen that in such a mass production there might be some part missing in the operation. Such missing operation parts contribute a lot in defect cost. There are two holes in an injector body- inlet hole and leak off hole with dia. 2.2 mm and 1.43 mm. These holes are gun-drilled into the forged body. Many times, it is observed that the drilling operation is incomplete, there might be many root causes for this like drill breakage, drill blunt, interruption in machine due to low coolant level, etc. Thus, there is a need for finding the dominant root cause and eliminate it. The BPS - one of the leading manufacturers in diesel system equipment has been successfully employing the efficient statistical tool ‘Shainin’ for the root cause identification and Design of Experiments (DOE) techniques for analysis and optimization of quality related issues. Shainin is popular being the simplest and effective tool to employ in solving manufacturing related problems. So, it was decided to select Shainin to find the dominant root cause. According to the theory that “there is a dominant cause of variation in the process output that defines the problem” and it is analogous to Pareto principle of ‘vital few and trivial many’ or ‘20/80 principle’, the Shainin system could be effectively used for solving the problem. The categorization of the problem was done in order to choose the best effective techniques such as Component search, Paired comparison, Concentration chart, Strategy diagram etc. The classification of the problem that is GreenY (as termed in Shainin® system) is done as Property, Profile, Defect, or Event. The event was subcategorized as destructive or malfunction event.

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