Designing of Bayesian Skip Lot Sampling Plan under Destructive Testing

Skip-lot sampling plan serves as a cost-effective technique to manage the cost of performing frequent product inspections. As a powerful tool within a real-time quality management system, the ability to collect data which an optimize skip-lot sampling parameters affords manufacturers the luxury of lowering inspection expenses in various manufacturing units. The good quality of product can be produced in continuous improvement of production process in excellent quality history for suppliers. The procedures and necessary tables are provided for finding the respective plans for which sum of producer and consumer risks are minimized with acceptable and limiting quality levels which accounts for the prior distribution of process state for each lot and revenue received appreciably which reduces destructive testing

OPTIMAL TESTING STRATEGIES FOR GENETICALLY MODIFIED WHEAT

A stochastic optimization model was developed to determine optimal testing strategies, costs, and risks of a dual marketing system. The model chooses the testing strategy (application, intensity, and tolerance) that maximizes utility (minimizes disutility) of additional system costs due to testing and quality loss and allows simulation of the risk premium required to induce grain handlers to undertake a dual marketing system versus a Non-GM system. Cost elements including those related to testing, quality loss, and a risk premium were estimated for a model representing a grain export chain. Uncertainties were incorporated and include test accuracy, risk of adventitious commingling throughout, and variety declaration. Sensitivities were performed for effects of variety risks, penalty differentials, re-elevation discounts, import tolerances, variety declaration, risk aversion, GM adoption, and domestic end-user.Segregation, Testing, Tolerance, Genetically Modified, Wheat, Risk Premium, Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

ISBIS 2016: Meeting on Statistics in Business and Industry

This Book includes the abstracts of the talks presented at the 2016 International Symposium on Business and Industrial Statistics, held at Barcelona, June 8-10, 2016, hosted at the Universitat Politècnica de Catalunya - Barcelona TECH, by the Department of Statistics and Operations Research. The location of the meeting was at ETSEIB Building (Escola Tecnica Superior d'Enginyeria Industrial) at Avda Diagonal 647. The meeting organizers celebrated the continued success of ISBIS and ENBIS society, and the meeting draw together the international community of statisticians, both academics and industry professionals, who share the goal of making statistics the foundation for decision making in business and related applications. The Scientific Program Committee was constituted by: David Banks, Duke University Amílcar Oliveira, DCeT - Universidade Aberta and CEAUL Teresa A. Oliveira, DCeT - Universidade Aberta and CEAUL Nalini Ravishankar, University of Connecticut Xavier Tort Martorell, Universitat Politécnica de Catalunya, Barcelona TECH Martina Vandebroek, KU Leuven Vincenzo Esposito Vinzi, ESSEC Business Schoo

Quality Assessment and Economic Sustainability of Translation

pp.15-38The concept of quality is mature and widespread. However, its associated attributes can only be measured against a set of specifications since quality itself is a relative concept. Today, the concept of quality broadly corresponds to product suitability – meaning that the product meets the user’s requirements. But then, how does one know when a translation is good? No answer can be given to this very simple question without recall to translation criticism and the theory of translation. However, the relationship between a source text and the translated text is unfit to solve the problem, as readers often perceive the endproduct of translation as the only material available for scrutiny; they have no interest in the translator’s decision-making process (the hermeneutic process). Therefore, translation adequacy should be taken into account in assessment especially when customers impose their own subjective preferences (requirements)

Reliability Testing and Verification

This chapter describes various methods for reduction of uncertainties in the determination of characteristic values of random quantities (quantiles of normal and Weibull distribution, tolerance limits, linearly correlated data, interference method, Monte Carlo method, bootstrap method)

A mathematical model for the product mixing and lot-sizing problem by considering stochastic demand

The product-mix planning and the lot size decisions are some of the most fundamental research themes for the operations research community. The fact that markets have become more unpredictable has increaed the importance of these issues, rapidly. Currently, directors need to work with product-mix planning and lot size decision models by introducing stochastic variables related to the demands, lead times, etc. However, some real mathematical models involving stochastic variables are not capable of obtaining good solutions within short commuting times. Several heuristics and metaheuristics have been developed to deal with lot decisions problems, in order to obtain high quality results within short commuting times. Nevertheless, the search for an efficient model by considering product mix and deal size with stochastic demand is a prominent research area. This paper aims to develop a general model for the product-mix, and lot size decision within a stochastic demand environment, by introducing the Economic Value Added (EVA) as the objective function of a product portfolio selection. The proposed stochastic model has been solved by using a Sample Average Approximation (SAA) scheme. The proposed model obtains high quality results within acceptable computing times

A Quality Systems Economic-Risk Design Theoretical Framework

Quality systems, including control charts theory and sampling plans, have become essential tools to develop business processes. Since 1928, research has been conducted in developing the economic-risk designs for specific types of control charts or sampling plans. However, there has been no theoretical or applied research attempts to combine these related theories into a synthesized theoretical framework of quality systems economic-risk design. This research proposes to develop a theoretical framework of quality systems economic-risk design from qualitative research synthesis of the economic-risk design of sampling plan models and control charts models. This theoretical framework will be useful in guiding future research into economic risk quality systems design theory and application