11 November 2004 Application of target costing in machining
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Proceedings Volume 5605, Intelligent Systems in Design and Manufacturing V; (2004) https://doi.org/10.1117/12.571657
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States
Abstract
In today's intensely competitive and highly volatile business environment, consistent development of low cost and high quality products meeting the functionality requirements is a key to a company's survival. Companies continuously strive to reduce the costs while still producing quality products to stay ahead in the competition. Many companies have turned to target costing to achieve this objective. Target costing is a structured approach to determine the cost at which a proposed product, meeting the quality and functionality requirements, must be produced in order to generate the desired profits. It subtracts the desired profit margin from the company's selling price to establish the manufacturing cost of the product. Extensive literature review revealed that companies in automotive, electronic and process industries have reaped the benefits of target costing. However target costing approach has not been applied in the machining industry, but other techniques based on Geometric Programming, Goal Programming, and Lagrange Multiplier have been proposed for application in this industry. These models follow a forward approach, by first selecting a set of machining parameters, and then determining the machining cost. Hence in this study we have developed an algorithm to apply the concepts of target costing, which is a backward approach that selects the machining parameters based on the required machining costs, and is therefore more suitable for practical applications in process improvement and cost reduction. A target costing model was developed for turning operation and was successfully validated using practical data.
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Bhaskaran Gopalakrishnan, Bhaskaran Gopalakrishnan, Ameet Kokatnur, Ameet Kokatnur, Deepak P. Gupta, Deepak P. Gupta, "Application of target costing in machining", Proc. SPIE 5605, Intelligent Systems in Design and Manufacturing V, (11 November 2004); doi: 10.1117/12.571657; https://doi.org/10.1117/12.571657
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