A dynamic programming model for designing a quality control plan in a manufacturing process

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Process quality planning should establish the quality control plan to achieve the desired quality level with the minimum quality cost (appraisal and failure costs) for the final product. This plan sets out the critical quality variables, the control stations in the process, and the control method at each control station. The quality costs associated with quality control and defective products can be greater than or less than ideal regarding the required quality level. The purpose of this paper is to provide a stochastic dynamic programming model for designing the quality control plan in a manufacturing process, which allows obtaining the desired level of control with the lowest cost. Inputs to the model are, in particular, control stations in the process, levels of quality, control methodologies (no control, statistical process control, 100% inspection), probabilities of changing the quality level and quality costs. The output of this model is the quality control plan that satisfies the desired level of quality at the lowest cost. This plan establishes the control stations, the methodology used in each control station, the desired quality level for the final product, and the estimated quality costs. Finally, an illustrative example based on a manufacturing process demonstrates the applicability of this approach and several considerations are reported about future research directions.FCT - Fundação para a Ciência e a Tecnologia(UID/CEC/00319/2019

Using cost of quality to select alternative suppliers and determine incoming inspection in dynamic contexts

Process quality planning should establish the incoming quality inspection plan to achieve the desired quality level with minimum Cost of Quality (CoQ). Additionally, the selection of alternative suppliers must be defined, and, in a dynamic context, the best solution may vary. The purpose of this study is to, through a simulation approach, minimize the total CoQ of two related decisions: i) supplier selection and ii) incoming quality inspection selection. We will determine the CoQ of alternative suppliers and determine the CoQ of alternative incoming inspections that are associated with such decisions. The inputs to the model are components costs, inspection costs, proportion of defectives from incoming lots, Type I and Type II inspection errors, alternative control methods, and the cost of delivering defective components to the manufacturing system. The uncertainty of some inputs is modelled through probability distributions and the dynamic context is modelled through different scenarios. The results from simulations estimate the total CoQ of each alternative decision. This model allows to determine the CoQ of the alternative scenarios and to define a best supplier and incoming quality inspection plan. A numerical example based on a manufacturing process demonstrates the applicability of this model and the results indicate that the optimal solution may vary when the model parameters are updated.(undefined

A Cost-Based Allocation of Inspection Efforts in Quality Control of a Multistage Assembly Line: A Case Study of an Electronics Assembly Line

Firms within the electronics manufacturing industry is often a high-volume high-mix product manufacturing industry. This study presents a cost-based allocation of inspection efforts in quality control of a sequential multi-stage electronic assembly line, considering all relevant costs and proposes the optimum inspection strategy. A dynamic sampling plan is incorporated in the model to maintain the desired quality levels. Monte-Carlo simulation is used to obtain the solution of this complex model. The model is created based on an actual electronics packaging company. This approach provides the ability to minimize the costs and does not sacrifice the quality of the products. The input factors that significantly affect the costs are identified so that they can be optimized for performance improvement and decision-making

An evolutionary algorithm and discrete event simulation for optimizing inspection strategies for multi-stage processes

The problem of determining the optimal inspection strategy for a given multi-stage production process, i.e. the inspection strategy that results in the lowest total inspection cost, while still assuring a required output quality, is modelled as a joint optimization of inspection location, type and inspection limits. A fusion between a discrete event simulation to model the multi-stage process subject to inspection and to calculate the resulting inspection costs, and an Evolutionary Algorithm (EA) to optimize the inspection strategies, is suggested

An evolutionary algorithm and discrete event simulation for optimizing inspection strategies for multi-stage processes

The problem of determining the optimal inspection strategy for a given multi-stage production process, i.e. the inspection strategy that results in the lowest total inspection cost, while still assuring a required output quality, is modelled as a joint optimization of inspection location, type and inspection limits. A fusion between a discrete event simulation to model the multi-stage process subject to inspection and to calculate the resulting inspection costs, and an evolutionary algorithm (EA) to optimize the inspection strategies, is suggested.Inspection allocation, Quality economics, Evolutionary algorithm, Discrete event simulation

Transient Performance Analysis of Serial Production Lines

TRANSIENT PERFORMANCE ANALYSIS OF SERIAL PRODUCTION LINES by Yang Sun The University of Wisconsin-Milwaukee, 2015 Under the Supervision of Professor Liang Zhang Production lines with unreliable machines and finite buffers are characterized by both steady-state performance and transient behavior. The steady-state performance has been analyzed extensively for over 50 years. Transient behavior, however, is rarely studied and remains less explored. In practice, a lot of the real production systems are running partially or entirely in transient periods. Therefore, transient analysis is of significant practical importance. Most of the past research on production systems focuses on discrete materials flow which utilities Markov chain analysis. This dissertation is devoted to investigate the effects of system parameters on performance measures for transient serial production line with other machine reliability models. The reliability models investigated in this dissertation are exponential and no-exponential (Weibull, Gamma, Log-normal). In a real production line system, machine reliability models are much more difficult to identify. Strictly speaking, it requires the identifications of the histograms of up- and downtime, which requires a very large number of measurements during a long period of time. The result may be that the machines\u27 real reliability model on the factory floor are, practically, never known. Therefore, it is of significant practical importance to investigate the general effects of system parameters on performance measures for transient serial production line with different reliability models. The system parameters include machine efficiency e, ratio of N and Tdown (K), machines\u27 average downtime Tdown, and coefficient of variation CV. The performance measures include settling time of production rate (t_sPR), settling time of work-in-process (t_sWIP), total production (TP), production loss (PL). The relationship between the performance measures and system parameters reveals the fundamental principles that characterize the behavior of such systems and can be used as a guideline for product lines\u27 management and improvement. Most previous research studies are limited to two or three machine system due to the technical complexity. Furthermore, presently there are no analytical tools to address the problems with multiple machines and buffers during transient periods. This dissertation addresses this problem by using simulations with C++ programming to evaluate the multiple machines (up to 10) and buffers and demonstrate the transient performance at different conditions. The simulation method does not only provide quantified transient performance results for a given production line, but also provides a valuable tool to investigate the system parameter effects and how to manage and improve the existing production line

IMPROVING FEEDBACK PROCESS FROM FINAL PRODUCT INSPECTIONS FOR CREATING CONTINUOUS IMPROVEMENT

Quality has costs, but bad quality is even more expensive. This is one of the reasons why improving quality via total quality management has become an essential part for manufacturing organizations globally. One of the most important subareas of total quality management is continuous improvement, which aims to continually correcting operations in a way, that it would create more value to the customer with smaller resources. This thesis is a case study to improve the feedback process from final product inspections commissioned by ABB Motors & Generators Vaasa. The thesis has been constructed with design science research -methodology. The aim of the thesis is to discover methods to improve the feedback process from the final product inspections and ultimately decrease the reclamation rates by applying recommended actions to the final inspection feedback process. Connections between improvements in feedback process and continuous improvement are investigated in this study. The research problem is How to improve feedback process from final product inspections and how to utilize the improved feedback the best way for creating continuous improvement? The results of this thesis indicate, that the feedback from final product inspections is considered highly important in the case organization. During the research, there were five improvement ideas to the feedback process found, which are quite easy to implement. It is challenging to say, whether the improvement ideas have an impact to the reclamation rates, but they were recognized as those practices, which should make the feedback loop more efficient in the future.Laatu maksaa, mutta huono laatu maksaa vielä enemmän. Tämä on yksi niistä syistä, miksi laadun parantaminen kokonaisvaltaisen laatujohtamisen avulla on kehkeytynyt välttämättömäksi osaksi teollisissa organisaatioissa maailmanlaajuisesti. Eräs tärkeä kokonaisvaltaisen laatujohtamisen aihe on jatkuva parantaminen, joka tähtää jatkuvasti korjaamaan toimenpiteitä siten, että sillä luodaan asiakkaalle lisää arvoa vähemmillä resursseilla. Tämä työ on tapaustutkimus tuotteiden lopputarkastusten palauteprosessin kehittämiseen ja toimeksiantaja on ABB Motors & Generators Vaasa. Työ on rakennettu käyttäen design science -tutkimusmenetelmää. Työn tavoitteena on löytää keinoja parantaa palauteprosessia tuotteiden lopputarkastuksista ja lopulta vähentää reklamaatioiden määrää soveltamalla suositeltuja toimia lopputarkastusten palauteprosessiin. Yhteyksiä jatkuvan parantamisen ja palauteprosessin kehittämisen välillä on tutkittu tässä työssä ja tutkimusongelma on Miten parantaa tuotteiden lopputarkastusten palauteprosessia ja kuinka hyödyntää parannettua palauteprosessia parhaalla mahdollisella tavalla jatkuvan parantamisen luomiseksi. Tutkimuksen tulokset osoittavat, että kohdeorganisaatiossa palautetta pidetään erittäin tärkeänä. Tutkimuksen aikana tunnistettiin viisi melko helposti jalkautettavaa kehitysideaa palauteprosessiin. On haasteellista sanoa, onko kehitysideoilla vaikutusta reklamaatioiden määrään, mutta ne tunnistettiin sellaisiksi toimintatavoiksi, joiden pitäisi tehdä palauteluuppi tehokkaampi tulevaisuudessa

Cost of quality tradeoffs in manufacturing process and inspection strategy selection

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 106-108).In today's highly competitive markets manufacturers must provide high quality products to survive. Manufacturers can achieve higher levels of quality by changing their manufacturing process and/or by product inspection where a multitude of different strategies are often available. Each option has its own cost implications that must also be taken into account. By reconciling the competing objectives of quality maximization and cost minimization, a cost of quality approach serves as a useful framework for comparing available manufacturing process and inspection alternatives. Still, any rigorous comparison requires both a metric as well as a profound understanding of cost of quality tradeoffs. The cost of quality tradeoffs in manufacturing process and inspection strategy selection are examined through a probabilistic cost of quality model explored analytically using a sample set of fundamental inspection strategies (reinspect rejects, reinspect accepts and single inspection) and applied to the case of electric vehicle battery pack assembly. From an expected value point of view a series of parametric sensitivity analyses reveal that complex tradeoffs between manufacturing process, inspection, internal and external failure costs determine the optimal manufacturing process and inspection strategy combination. In general, reinspect rejects minimizes internal failure costs, reinspect accepts minimizes external failure costs and single inspection lies in between while minimizing inspection costs. This thesis illustrates the fact that results are scenario specific and depend on product cost-, manufacturing process and available inspection method attributes. It is also observed that manufacturing process improvement often coincides with a need to change inspection strategy choice, thereby indicating that manufacturing process and inspection strategy selection should not be performed independently of each other. This thesis demonstrates that the traditional expected value approach for evaluating cost of quality implications of manufacturing and inspection is often misleading. Decision tree formulations and discrete event simulations indicate that cost of quality distributions are asymmetric. High internal- and external failure costs, manufacturing process non-conformance rates and inspection method error rates are contributing factors. The alternative metric of expected utility captures decision makers risk aversion to high cost outliers and changes the criteria for optimality and favors inspection strategies and manufacturing processes that minimize external failure events with increasing risk intolerance. In the examined case of electric vehicle battery pack assembly both material- and external failure costs are very high. Analytical and discrete event simulation results indicate that for the given welding process the inspection strategy that minimizes external failure costs is optimal from an expected cost point of view as well as at high degrees of risk aversion. This result is shown to be sensitive to parameters driving the cost and probability of external failure events.by Hadi Zaklouta.S.M