Product Quality Inspection By: Erik Martin Penn Sate University What will be covered This presentation deals with the question of describing and evaluating product quality inspection processes. What is to be discussed Classification of characteristics proposed for describing the effects of industrial processes. Formulation of definitions of the effectiveness and efficiency coefficients of quality inspection processes. Practical examples of effectiveness and efficiency analysis, using numerical data. Designating the effects of the process Ontological designations -describe the effect of the process in respect of quantity, quality, or financial value. Axiological -the determination of the relative worth of the process results. Organizational usefulness Using some simple mathematical equations and some data from earlier productions, one can use those particular figures to demonstrate the practical usefulness of the characteristics of the effectiveness of the quality inspection process. How it works Taking concepts and data; inspection processes are very important in many companies. Notation for the main characteristics of the quality inspection process. Of(0), If(0) - are, respectively, the rejection losses and the total outlay for the inspection and preventive actions in the previous calculation period. OFA, IFA - are the expected losses and planned outlay in the present period. OFP, IFP - are the actual losses and costs in the present period. Selection of the most effective or the most efficient system of inspection and preventive action. Designations of the process Type of designation assessment effectiveness Efficiency ontological Ex-ante EOA= Of(0) - OFA SOA = OF(O) –OFA/ IFA ontological Ex-post EOB= OF(0) - OFP SOB=OF(O) –OFP/ IFP axiological Ex-post EAB = OF(O)-OFP/ OF(O) - OFA SAB = (SOB)(SOA) The mathematical model for the optimization of the effectiveness of a quality inspection process takes 2 forms. Minimize the total expected loss OFA Maximize the expected efficiency SOA Examples of 2 quality inspection processes process A Number of the production phase Process fraction defective Actual inspection operation Actual rejection probability Actual outlay 1 .2 None 0 0 2 .2 None 0 0 3 .3 Type 3 8 300 Second example Process B Number of the production phase Process fraction defective Actual inspection operation Actual rejection probability Actual outlay 1 0 none 0 0 2 .077 Type 2 .95 166,490 3 .087 Type 2 .932 224,130 4 .073 Type 2 .947 427,200 Actual values of the outlay and the rejection losses in the previous period were Process A : IFP = 300; OFP = 4790 Process B : IFP = 817,820 OFP= 5,282,180 Results of investigations Production process Expected Obtained effectiveness Efficiency effectiveness Efficiency EOA SOA EOB / EAB SOB / SAB A 345.6 1.15 170 / .49 .57 / .49 B 25,481,000 31.16 25,528,820 / 1.00 31.22 / 1.00 Conclusion of process A The actual system of inspection operations for the production process A is both ineffective, since the real effect is half as high as the expected result, and inefficient, since the decrease in the rejection losses is lower than the outlay for the inspection performance; the real efficiency is half as high as the expected result. Conclusion of process B The actual organization of the quality inspection is much better: the real effect is nearly equal to the expectations (EAB = 1); the efficiency of quality inspection is both near to the expected efficiency (SAB = 1) and also high in absolute numbers (SOB = 31.22, I.e. one unit of the outlay produces 31 units of the effect, which means a reduction in losses. summary Quality inspection is useful Quality inspection is effective Quality inspection is efficient Quality inspection is necessary references Hall, M. and Winsten, C., 1965. A dictionary of the Social Sciences. New York. Lubicz, M., 1983. On the problem of optimization of a quality inspection process structure.. Int. J. Prod. Res., 21(3): 369. Lubicz, M., 1979. Investigations of decision premises for product quality formation. Ph. Thesis, Techn. Univ. Wroclaw. Milward, G.E., 1960. Organization and Methods. MacMillan, London.