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Byline: Isak. Wahlstedt, Nikolaj. Jensen This study investigates whether patient safety can be enhanced by the implementation of an automated electronic checklist (PlanCheck) for physics quality control review (QCR) of [...]

This paper provides a quantitative and comparative economic and risk approach to strategic quality control in a supply chain, consisting of one supplier and one producer, using a random payoff game. Such a game is first solved in a risk-neutral framework by assuming that both parties are competing with each other. We show in this case that there may be an interior solution to the inspection game. A similar analysis under a collaborative framework is shown to be trivial and not practical, with a solution to the inspection game being an 'all or nothing' solution to one or both the parties involved. For these reasons, the sampling random payoff game is transformed into a Neyman--Pearson risk constraints game, where the parties minimize the expected costs subject to a set of Neyman--Pearson risk (type I and type II) constraints. In this case, the number of potential equilibria can be large. A number of such solutions are developed and a practical (convex) approach is suggested by providing an interior (partial sampling) solution for the collaborative case. Numerical examples are developed to demonstrate the procedure used. Thus, unlike theoretical approaches to the solution of strategic quality control random payoff games, the approach we construct is both practical and consistent with the statistical risk Neyman--Pearson approach. doi: 10.1057/palgrave.jors.2602420 Published online 16 May 2007 Keywords: quality control; game theory; supply chains

Acceptance sampling plans provide the vendor and the buyer decision rules for lot sentencing to meet their product quality needs. A problem the quality practitioners have to deal with is the determination of the critical acceptance values and inspection sample sizes that provide the desired levels of protection to both vendors and buyers. As today's modern quality improvement philosophy, reduction of variation from the target value is the guiding principle as well as reducing the fraction of defectives. The [C.sub.pm] index adopts the concept of product loss, which distinguishes the product quality by setting increased penalty to products deviating from the target. In this paper, a variables sampling plan based on [C.sub.pm] index is proposed to handle processes requiring very low parts per million (PPM) fraction of defectives with process loss consideration. We develop an effective method for obtaining the required sample sizes n and the critical acceptance value [C.sub.o] by solving simultaneously two nonlinear equations. Based on the designed sampling plan, the practitioners can determine the number of production items to be sampled for inspection and the corresponding critical acceptance value for lot sentencing. doi: 10.1057/palgrave.jors.2602013 Keywords: acceptance sampling plans; decision making, fraction of defectives; probability density function; process capability indices; quality control

Loepfe solutions and services for the textile industry are recognized as being innovative and leading in application technology. Loepfe plays a major role in the field of electronic clearers, which [...]

When looking for a new physician, patients often are encouraged to select those who are board-certified or who have not made payments on malpractice claims. These characteristics are not always [...]

A recent article in The Lancet analysed the barriers to reaching the Millennium Development Goals (MDGs) concerning maternal health, child health, tuberculosis, malaria and human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS). [...]

Issues concerning the quality problems in higher education following the reduction in student funding are discussed. Particular emphasis is given to reports from the Quality Assurance Agency regarding the decrease in quality standards in higher education.