Authors: Bimal Nepal, Bharatendra K. Rai
Addresses: Industrial Distribution Program, Dwight Look College of Engineering, Texas A&M University, 3367 TAMU, College Station, Texas 77843-3367, USA. ' Department of Decision and Information Sciences, Charlton College of Business, University of Massachusetts – Dartmouth, 285 Old Westport Road, North Dartmouth, MA 02747-2300, USA
Abstract: Colour sample manufacturing industry provides an important support for the paint manufacturers. It manufactures colour samples that help original paint manufacturers to sell paint by allowing potential customers to accurately visualise a specific colour. One of the burning issues in colour sampling manufacturing is accurately predicting the tally gallons. It involves an estimation of paint volume to cover a given surface area of paper. The as-is tally gallons estimation process is rudimentary and largely depends upon the human experience. Ideally, this quantity should be enough to cover the target surface area regardless of colour appearance. However, this is not the case with existing process. Currently, lighter colours run out in the middle of the production run while darker colour appearances have significant amount of left over paint. The amount of painting waste is as high as 15% (by volume) in some cases. The objective of this paper is to present a predictive model to better estimate the tally gallons by minimising painting waste. It presents a case study of a US colour sample manufacturing company. The results show that the proposed multiple linear regression approach reduces the leftover paint significantly.
Keywords: process excellence; colour sample manufacturing; tally gallons; paint waste; case study; colour samples.
International Journal of Business Excellence, 2010 Vol.3 No.2, pp.186 - 205
Available online: 01 Jan 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article