DESIGNING FOOD SAFETY REGULATIONS: THE EFFECT OF INSPECTION POLICY AND PENALTIES FOR NONCOMPLIANCE ON FOOD PROCESSOR BEHAVIOR

In the United States, federal, state, and local governments are involved with the regulation of the safety of the food supply. Food safety regulations that set standards for food processors usually include inspection policies for monitoring performance and penalties for processors who do not comply with regulatory standards. In this analysis, we examine how penalties and inspection policies interact to influence processor behavior. We distinguish between internal penalties (imposed by the regulator) and external penalties (imposed by the market or by the court). Using a model of the processor's expected annual cost, we find that under a given inspection policy internal penalties are only relevant under specific conditions. For cases in which internal and external penalties can be influenced, we use comparative statics to discover that internal penalties are more economically efficient for motivating processors than external penalties. These results imply that regulators should utilize internal penalties for noncompliance rather that rely on market or court-imposed penalties.Food Consumption/Nutrition/Food Safety,

Rectifying Sampling Inspection by Variables or Attributes? Combined Inspection

Acceptance sampling, one of the techniques used in quality control, is analysed in present paper. We shall study sampling inspection plans when the remainder of a rejected lot is inspected, i.e. rectifying plans. These plans were introduced by Dodge and Romig for inspection by attributes (each inspected item is classified as either good or defective). Analogous rectifying plans for inspection by variables with one specification limit for the quality characteristic were introduced by the author of this contribution. In present article we shall consider combined inspection (all items from the sample are inspected by variables, but remainder of a rejected lot is inspected only by attributes). We shall show that the combined inspection is the best in many situations. Using plans for combined inspection we can often achieve significant savings of the inspection cost under the same protection of producer and consumer

Estimation of the lot fraction defective in a finite lot of products with auxiliary quality characteristics

Many companies use sampling plans for the acceptance or rejection of lots of prod-ucts. The final o utcome o f t his d ecision-making p rocess i s b ased o n t he i nspection of a sample of products selected from a lot under inspection, where a quality character-istic is observed. An important parameter of interest related to acceptance sampling for attributes is the proportion of defective items. This parameter is unknown for a given lot of products, but it can be estimated from the aforementioned sample infor-mation. Additional quality characteristics can be observed at the inspection stage. We propose to use this auxiliary information to obtain more accurate estimators of the lot fraction defective at the estimation stage. Various relevant applications of this process are described. For possible scenarios that may arise in practice, the empirical properties of the suggested estimation methods are investigated using Monte Carlo simulations, and desirable results are obtained when there is a strong relationship between the quality characteristic of interest and the auxiliary quality characteristic

A family of group chain acceptance sampling plans based on truncated life test

Acceptance sampling is a statistical quality control procedure used to accept or reject a lot, based on the inspection result of its sample. For high quality products, zero acceptance number is considered and the life test is often terminated on a specific time, hence called truncated life test. A plan having zero acceptance number is deemed unfair to producers as the probability of lot acceptance drops drastically at a very small proportion defective. To overcome this problem, chain sampling which uses preceding and succeeding lots information was introduced. In ordinary chain sampling plans, only one product is inspected at a time, although in practice, testers can accommodate multiple products simultaneously. In this situation, group chain sampling plan with small sample size is preferred because it saves inspection time and cost. Thus, it is worthwhile to develop the various types of chain sampling plans in the context of group testing. This research aims to develop new group chain (GChSP), modified group chain (MGChSP), two-sided group chain (TS-GChSP) and modified two-sided group chain (TS-MGChSP) sampling plans using the Pareto distribution of the 2nd kind. These four plans are also generalized based on several pre-specified values of proportion defective. This study involves four phases: identifying several combinations of design parameters; developing the procedures; obtaining operating characteristic functions; and measuring performances using both simulated and real lifetime data. The constructed plans are evaluated using various design parameters and compared with the established plan based on the number of minimum groups, and probability of lot acceptance,. The findings show that all the proposed plans provide smaller and lower compared to the established plan. All the plans are able to reduce inspection time and cost, and better at protecting customers from receiving defective products. This would be very beneficial to practitioners especially those involved with destructive testing of high quality products

Measuring the Regional Dimension of Innovation through an Economic Model Based on Rectifying Technology Audits according to the AICTT-RTA Protocol

The aim of this paper is to give an answer to the question "how to detect the regional dimension of innovation?". So, in this paper, a method to be used as an operational tool that is able to grasp regional specificities in the innovation process, based on the optimization of measurement activity, is proposed. Evidence in the scientific literature shows that data and indicators are able to quantify the contribution of different regions, identify the different technological profiles of the regions and measure the technological performances of regional systems, the innovative performances of firms and the density and quality of systemic interactions between the main institutional actors, but these items are often not developed through an analytical model of measure control cost based on the optimization of certain influencing factors. The proposed approach is based on two main points: 1) Define the opportune methodology to detect the innovation level of a single firm. For this aim it has been considered the AICTT-RTA protocol. Each SME, is considered as innovative or as non-innovative according to the outcome of a Technology Audit (TA) conducted in compliance with the AICTT-RTA protocol. 2) Determine, starting only from some of the SMEs in a certain monitored area, if the entire area is innovative or not, through TA on a optimal sample size of SMEs analyzed. For this second point the approach uses a bayesian analysis of the Deming cost model. This approach considers a wide area, industrial or urban, in which SMEs are present and treats it as a lot of N items. Through the proposed approach, to characterize the regional innovation it's sufficient to characterize just only some SMEs, however detecting the whole regional innovation profile. In this paper this aspect is valorized and set in the form of a useful operational tool for regional institutions, innovation managers, entrepreneurs and researchers. Simulation results complement the proposed theoretical model

A particle swarm algorithm for inspection optimization in serial multi-stage processes

AbstractImplementing efficient inspection policies is much important for the organizations to reduce quality related costs. In this paper, a particle swarm optimization (PSO) algorithm is proposed to determine the optimal inspection policy in serial multi-stage processes. The policy consists of three decision parameters to be optimized; i.e. the stages in which inspection occurs, tolerance of inspection, and size of sample to inspect. Total inspection cost is adopted as the performance measure of the algorithm. A numerical example is investigated in two phases, i.e. fixed sample size and sample size as a decision parameter, to ensure the practicality and validity of the proposed PSO algorithm. It is shown that PSO gives better results in comparison with two other algorithms proposed by earlier works

Models for the Economic Allocation of Sampling Inspection Effort in Multi-Stage Production Systems.

Appropriate inspection and control are significant components of production systems. Many products are manufactured in multistage production lines. At each stage the process can produce defective units. In order to produce finished products with desired quality in an economical way, considerations must be given to the explicit costs of inspection, repair, processing and disposal associated with particular levels of control and inspection. In this dissertation models and solution techniques are developed for simultaneous selection of sampling inspection plans and manufacturing operations control levels within multistage production systems. Per unit expected minimum cost of output quality, which satisfies specified consumer\u27s and producer\u27s risks, is used as the optimization criterion. The solution techniques allow for solving models with non-linear cost functions. Three different models are developed for three different situations. A model for situations where the defective items are not repairable is considered first. This is followed by a model for situations where the defective items are repairable and the number of defects and the types of defects are significant factors in computing repair costs. In the third model the effect of inspection errors is considered. The solution techniques are based on the forward recursion of dynamic programming and a numerical search method. Computer programs for solving all three models are presented

Design of Variables Sampling Plan in Agro-Allied Industry for Packed Yam Flour in-view of International Regulatory Standards

To stay competitive in today’s global market, manufacturers must ensure products released to consumers, meet international regulations and standards and this can only be done by putting in place sampling plans to guarantee the release of quality lots of products into the market. Hence, the objective of this paper is to design a variables sampling plan for the released of packed yam flour in view of international regulations on the net content of packaged goods. Probability plots, operating characteristic curves, the average outgoing quality (AOQ), average outgoing quality limit (AOQL) and average total inspection (ATI) were useful measures to evaluate the fitness of the sampling plan using the Minitab 2021 statistical software package. The packing process net weight, was found to be normally distributed with a p-value of 0.075 and a process standard deviation of 2.16. A comparative analysis on sample size, sampling plan measures, such as the AOQ, AOQL, and ATI and in view of best practice, were decisive in selecting a sampling plan with a sample size of 31 packs per lot as the most economic plan for lot sentencing. A practical demonstration on this sampling plan usage was also showcased. This sampling plan elevates and improves the net content of the packed product released into the market in view of international regulatory laws

Conception conjointe des politiques de contrôle de production, de qualité et de maintenance des systèmes manufacturiers en dégradation

RÉSUMÉ : La gestion de la production, le contrôle de la qualité et la planification de la maintenance sont les trois principales fonctions de la gestion des opérations dans les usines manufacturières. Dans la pratique, ces trois fonctions sont souvent gérées séparément, bien qu’elles soient, en réalité, étroitement inter-reliées. Plusieurs recherches ont été menées depuis des décennies afin de concevoir et d’optimiser conjointement les politiques de contrôle de la production, de la qualité et de la maintenance. Cette tendance est motivée par le fait que les politiques d’intégration des trois fonctions permettent d’améliorer la productivité et de réduire considérablement les coûts. Cependant, dans la quasi-totalité des modèles d’intégration dans la littérature, seulement deux fonctions sont intégrées à la fois. De plus, pour des raisons de simplification, ces modèles sont basés sur certaines hypothèses simplificatrices et irréalistes pour modéliser la dégradation de la qualité des produits et de la fiabilité des machines. Par exemple, ces modèles négligent souvent l’impact des opérations de production sur l’intensité de dégradation, mais aussi la corrélation entre les dégradations de la qualité et de la fiabilité. Par ailleurs, les politiques de contrôle de la qualité utilisées dans ces modèles sont soit les cartes de contrôle, soit le contrôle à 100%. Toutefois, l’intégration des plans d’échantillonnage, qui représentent une branche importante de Contrôle Statistique de la Qualité, avec les politiques de production et de maintenance n’a pas été étudiée encore dans la littérature. Ces plans sont largement utilisés dans l’industrie depuis longtemps afin d’éviter le coût excessif du contrôle à 100% et d’assurer en même un contrôle statistique de la qualité des produits livrés. Cette thèse s’intéresse au problème de conception conjointe des politiques de contrôle de la production, de la qualité et de la maintenance. L’objectif principal de la recherche est d’intégrer les plans d’échantillonnage avec les politiques de production et de maintenance des systèmes où la qualité et la fiabilité sont les deux sujettes à la dégradation. Nous proposons une approche pratique de modélisation et d’optimisation de ces politiques qui permet de prendre en considération la dynamique complexe de la dégradation telle que dans la réalité des systèmes manufacturiers. En outre, nous étudions les propriétés statistiques des plans d’échantillonnage afin de montrer comment des informations pertinentes fournies par ces plans peuvent être intégrées dans la planification des activités de maintenance préventive afin d’améliorer les performances globales des systèmes manufacturiers. Les contributions scientifiques réalisées dans le cadre de cette thèse sont présentées sous forme de quatre articles de revue. Le premier article introduit un modèle d’intégration du plan d’échantillonnage simple avec la commande de la production pour un système de fabrication par lots. Ce modèle vise essentiellement à étudier les interactions entre les paramètres du plan d’échantillonnage et les paramètres de gestion de la production tels que la taille du lot de production et le stock de sécurité. Ensuite, une extension de ce modèle est proposée dans le deuxième article afin de considérer l’aspect dynamique de la dégradation de la qualité et de la fiabilité en fonction des opérations de production et d’intégrer une politique de maintenance préventive. L’objectif est d’optimiser conjointement les paramètres de contrôle de la production, de la qualité et de la maintenance de façon à minimiser le coût total des opérations, tout en respectant une contrainte sur la qualité après-contrôle. De plus, cet article vise à montrer l’utilité des informations issues du plan d’échantillonnage simple pour la surveillance de la qualité de la production et pour l’organisation des actions de maintenance préventive. Une analyse comparative de l’utilisation de plan d’échantillonnage par rapport au contrôle à 100% est aussi fournie afin de quantifier les gains économiques qui en découleraient. Le troisième article propose une approche d’intégration du plan d’échantillonnage continu de type-1 (CSP-1) avec les politiques de production et de maintenance préventive pour les systèmes de production continue. L’objectif est d’étendre l’applicabilité du plan CSP-1 aux processus de production en dégradation, puisqu’il est actuellement applicable seulement aux processus stables. Un autre objectif de cet article est de quantifier les bénéfices de l’utilisation de CSP-1 par rapport au contrôle à 100%, et de montrer aussi comment le couplage de CSP-1 avec la maintenance préventive permet d’améliorer les performances des systèmes en dégradation. Finalement, le quatrième article introduit un modèle de contrôle conjoint de la production, de la qualité et de la maintenance d’une ligne de production dont les machines sont sujettes à la dégradation. En plus, les machines peuvent tomber en panne à cause des pièces non-conformes fabriquées dans les processus en amont. L’objectif est de montrer l’importance de la corrélation entre les dégradations de la qualité et de la fiabilité dans la modélisation de la dynamique des systèmes manufacturiers, et d’étudier l’effet de cette corrélation sur les paramètres optimaux du contrôle de la production, de la qualité et de la maintenance. Le second objectif de cet article est de montrer que les activités de maintenance et de contrôle de la qualité à un certain niveau de la ligne de production contribuent aussi à l’amélioration de la fiabilité des machines en aval.----------ABSTRACT : Production, quality and maintenance control are the three main functions of operations management in manufacturing plants. Traditionally, they have been treated by scientists and practitioners as separate problems even though they are strongly interrelated. In the past three decades, the integration of production, maintenance and quality control has attracted much attention in the literature. This trend is motivated by the fact that integrated control policies generally result in better manufacturing performance and significant cost savings. Nevertheless, most of the existing integrated models in the literature integrate only two functions at a time. Moreover, for simplicity, almost all of the integrated models are based on several simplifying assumptions that may make them unrealistic. For example, the complex dynamics of quality and reliability degradations such as the impact of operations speed on degradation intensity and the correlation between quality and reliability degradations have been always overlooked in the literature of integrated models. On the other hand, the quality control policies used in the existing integrated models are either 100% inspection of all parts produced or statistical process control tools such as the control charts. However, acceptance sampling which constitutes an important branch of the Statistical Quality Control has never been integrated with production and maintenance policies. Acceptance sampling plans and procedures have been widely used in industry for a long time to reduce the cost and time of quality inspection and to statistically control the outgoing quality. This research considers the problem of the joint design of production, quality and maintenance control policies of stochastic manufacturing systems. Specifically, the main objective of this thesis is to integrate sampling inspection techniques with production and maintenance control policies for systems subject to both quality and reliability degradations. We provide a practical modeling framework to adequately pattern the complex dynamics of degradation processes as in the real-life in order to develop new effective integrated control policies. Moreover, we investigate the intrinsic statistical properties of acceptance sampling plans in order to demonstrate how they can be coupled with condition-based maintenance to improve the overall performance of degrading manufacturing systems. This thesis is comprised of four journal articles. The first article investigates the joint production and quality control of a batch-processing production system which is unreliable and imperfect. A single acceptance sampling plan by attributes is used for quality control. The objective of this article is to introduce an integrated model for the joint optimization of the production lot size, the safety stock and the sampling plan parameters which minimize the total cost incurred. This aims to provide a better understanding of the interactions between the optimal production-inventory settings and the optimal sampling plan parameters. As an extension of this model, the second article considers that quality and reliability degradations are operation-dependent. Moreover, a preventive maintenance strategy is incorporated into the integrated control policy. Thus, the objective is to jointly optimize the production, quality and maintenance control parameters. This article investigates the statistical characteristics of the single sampling plan to show the relevance of quality information resulting from such a quality control to the maintenance decision-making. Also, a comparative study is conducted to quantify the economic savings that can be realized by using the sampling plans for degrading systems rather than 100% inspection. The third article addresses the joint economic design of production control, type-1 continuous sampling plan (CSP-1) and preventive maintenance of continuous-flow manufacturing systems. The objective is to show how integrated control policies can extend the application of continuous sampling plans to degrading production systems, as they are presently limited only to stable processes. In this article, three quality control policies are considered and compared: 100% inspection, the classical CSP-1 as in the standard procedures and a CSP-1 plan with a stopping rule that is coupled with condition-based maintenance. This aims to quantify the economic savings that can be achieved by using the CSP-1 compared to 100% inspection and to demonstrate how CSP-1 with an inspection stopping rule for degrading processes is more cost-effective than the classical CSP-1. Finally, the fourth article investigates the joint design of production, quality and maintenance control policies for manufacturing lines. We consider a small production line composed of two machines subject to quality and reliability degradations. The second machine is also subject to failures caused by defective products manufactured in upstream processes. The main objective of this article is to study the interactions between the optimal production, quality and maintenance control settings and the effect of failures correlation on those settings. Also, we show how maintenance and quality control activities in preceding stages can play an important role in the reliability improvement of the subsequent machines