The Use of Statistical Methods for Economic Control of Quality in Industry

Abstract

There are some indications that the competitive advantage of low-priced labor, which the South has long enjoyed, will become less important in the future. Minimum wage laws have narrowed somewhat the gap between the most poorly paid workers in the North and in the South. Progress in unionization will no doubt tend to narrow the gap of average wage rates. Many people look forward to a lowering of tariff barriers after the war. Some argue that this will hurt American industries in which a large proportion of the cost of production is unskilled labor. This might mean, for instance, a decline in textile manufacturing in the South because of competition with the Orient, and perhaps with other regions. Some of these regions will have not only low-priced labor, but also the latest and best equipment which American industry can produce. It is quite possible, therefore, that the future of Southern industry will depend to an increasing degree on (1) its ability to obtain a large output per unit of physical input, and (2) the quality of its output. Manufacturers have always tried to control the quality of their output, and have even made use of samples to check on their current process and to assist in deciding whether to accept or reject a shipment of goods. But the use of statistical theory in making logical inferences concerning the quality of goods being manufactured, or the shipment received, on the basis of small random samples is relatively new.'