The Value of Improved Measurements in a Pig Slaughterhouse

The pig industry is an essential and important part of Danish economy with an export value in 2006 of more than DKK 28 billions [Danish Meat Association (2007)]. The competition is hard, and potential new competitors from low cost countries can be expected to enter the traditional Danish export markets.

Therefore it is more important than ever to optimize all aspects of Danish pig production, slaughtering processes and delivery. This paper concerns the aspects of optimization at the slaughterhouses regarding estimation of the value of improved measurements. The slaughterhouse industry differs from the traditional industry in a number of ways.

There is a large natural variation in the raw materials regarding quality, weight, size, lean meat percentage, as a consequence of pigs being a biological material. The slaughterhouses handle this large variation by sorting the pigs into groups consisting of pigs with almost the same characteristics and thereby reducing the variation within the individual sorting groups substantially.

The accuracy of the measurements is the most important limiting factor for how much the variation within each sorting group can actually be reduced. Substantial investments are expected to improve the quality of the measurements further. This paper concerns the use of Operations Research to solve a practical problem, which is of major importance for the industry, namely to improve the estimation of the economic effects of improved measurements.

The benefit for the industry is obviously to be able to decide upon the level of measuring accuracy worth investing in. The main conclusion is that even relatively simple optimization models can advantageously be used to improve the basis of the slaughterhouses for making decisions regarding improved measurements.

The model is a Mixed Integer Programming (MIP) model and is used to compute the consequences of improved measurements and analyze different scenarios regarding restrictions in sales volume and quality restrictions. The assumptions regarding pricing and cost are found to be very important to obtain a true and fair view of the size of the profit.

For future (and improved) computations the net prices used can advantageously be split into 3-4 different contributions, which should be estimated separately for each product.