Joint production, quality and maintenance control of a two-machine line subject to operation-dependent and quality-dependent failures

Bouslah, Bassem; Gharbi, Ali; Pellerin, Robert

doi:10.1016/j.ijpe.2017.10.016

Cited by 88 publications

(33 citation statements)

References 38 publications

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“…For Montgomery (2004), statistical quality control techniques can be applied in industrial and non-industrial processes, in order to detect and correct the anomalies in the process to meet the specified target of a given product. For Duarte and Saraiva (2008), Toledo et al (2008) and Bouslah et al (2018), the SPC is an important management tool for improving quality and increasing the productivity of industrial processes, used to reduce the variability process.…”

Section: Introductionmentioning

confidence: 99%

Control chart based on residues: Is a good methodology to detect outliers?

et al. 2019

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The purpose of this article is to evaluate the application of forecasting models along with the use of residual control charts to assess production processes whose samples have autocorrelation characteristics. The main objective is to determine the efficiency of control charts for individual observations (CCIO) and exponentially weighted moving average (EWMA) charts when they are applied to residuals of models of AR(1) or MA(1) to detect outlier in autocorrelated processes. Considering autocorrelation strength and sign in the data series and the outlier range, the series were simulated accomplishing 640,000 sets. The series were contaminated by anomalous observations at 100th position, an AR(1) or MA(1) model were fitted, and the residuals were evaluated by CCIO and EWMA control charts; the points correctly detected as an autocorrelation were recorded. For the parameters investigated (autocorrelation and outlier range), a detection rate was generated in each chart, and nonparametric comparison tests were applied. The result of the tests showed the superiority (p < 0.05) of the CCIO chart for both models. The study of the influence of the sign and magnitude of the autocorrelation parameter showed no significant (p > 0.05) for either AR(1) or MA(1) charts and models. In this context, control charts for individual observations (CCIO) were confirmed to effectively detect outliers through residuals in industrial autocorrelated processes originated in first-order AR and MA models.

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Section: Introductionmentioning

confidence: 99%

Control chart based on residues: Is a good methodology to detect outliers?

et al. 2019

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“…Policy-II: This paper is derived from the results of Bouslah et al [30], where the production planning does not implement a JIT strategy. The production strategy consists only of the determination of an optimal inventory threshold level Zp o , which is constant during the entire time horizon.…”

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confidence: 99%

JIT Production Strategy and Maintenance for Quality Deteriorating Systems

et al. 2019

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We study the optimal production planning and major maintenance scheduling for an unreliable manufacturing system. We assume that the production unit experiences progressive deterioration that negatively influences product quality. For the production policy, we extend improve traditional threshold policies with a superior alternative, based on a just-in-time (JIT) strategy. The paper brings a new vision on the importance of implementing more effective production strategies based on JIT methods, instead of traditional threshold policies. When a failure occurs, the production unit is minimally repaired, and when the major maintenance is selected, the machine is restored to brand-new conditions. The objective of the model is to determine the simultaneous JIT production and major maintenance strategy that minimizes the total cost. Due to the stochastic features of the system, a simulation-based optimization approach is proposed, which combines the descriptive capabilities of simulation modeling with analytical models, statistical analysis, and optimization techniques. The results verify that the proposed simulation–optimization approach provides new and coherent results that highlight the strong influence of quality deterioration on the determination of the control parameters. A sensitivity analysis and a comparative study are conducted to illustrate that significant cost savings could be obtained with the proposed approach.

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“…The research work of Bouslah et al has jointly optimized production, quality control and maintenance for a production line. 14 Their study consists in proposing a combination of a mathematical model and simulation to simultaneously determine the optimal values of three decision variables: PM age, quality control level and inventory level. In the same way, Tam et al studied the problem of integrated maintenance planning in production, the objective is to determine an optimal production and PM plan, while simultaneously minimizing production and PM costs.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated planning of production and maintenance for imperfect system with subcontracting strategies

Hafidi¹,

Barkany²,

Mhamedi

et al. 2020

International Journal of Engineering Business Management

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The purpose of this article is to deal with subcontracting strategies in the context of production, maintenance and quality integration. We study the multi-item capacitated lot-sizing problem for a production system composed of a single machine. The production system is considered imperfect, producing both conforming and non-conforming items. However, the deterioration of the system is a function of the time and production rate, which affects the quality of the manufactured items. Consequently, a quality control strategy is established, the aim is to inspect, adjust and control the manufactured items. To solve our problem, an evolutive optimization approach is proposed, namely the genetic algorithm (GA). Then, in order to adjust the parameters of GA, we use the Taguchi method. This article is one of the few documents dealing with integrated production management, maintenance and quality under subcontracting constraints that takes into account the complex aspect of the multi-item manufacturing industry. Then, a sensitivity analysis is also carried out to illustrate the robustness of the proposed control policy. Finally, we compare our results with the literature to validate our approach and highlight the advantage of subcontracting in minimizing costs.

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Joint production, quality and maintenance control of a two-machine line subject to operation-dependent and quality-dependent failures

Cited by 88 publications

References 38 publications

Control chart based on residues: Is a good methodology to detect outliers?

Control chart based on residues: Is a good methodology to detect outliers?

JIT Production Strategy and Maintenance for Quality Deteriorating Systems

Integrated planning of production and maintenance for imperfect system with subcontracting strategies

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