A new approach to deal with learning in inspection in an integrated vendor-buyer model with imperfect production process

Dey, Oshmita; Giri, Bibhas C.

doi:10.1016/j.cie.2018.12.028

Cited by 34 publications

(9 citation statements)

References 41 publications

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“…In addition, learning and forgetting are studied as two of the most important factors in productivity. There are some studies that examine the effects of process learning and forgetting on the grouping of orders, lot-sizing, batch sequencing and number of the shipments (Castellano et al, 2019;Teyarachakul et al, 2016;Pei et al, 2017;Dey and Giri, 2019). In the present study, we integrate job rotation with the line balancing and sequencing problem, and consider heterogeneous operators, where their performance is impacted by the length and frequency of the job rotations.…”

Section: Literature Reviewmentioning

confidence: 99%

The job rotation scheduling problem considering human cognitive effects: an integrated approach

Ayough

Farhadi

Zandieh

2021

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Purpose This paper aims to unfold the role that job rotation plays in a lean cell. Unlike many studies, the authors consider heterogeneous operators with dynamic performance factor that is impacted by the assignment and scheduling decisions. The purpose is to derive an understanding of the underlying effects of job rotations on performance metrics in a lean cell. The authors use an optimization framework and an experimental design methodology for sensitivity analysis of the input parameters. Design/methodology/approach The approach is an integration of three stages. The authors propose a set-based optimization model that considers human behavior parameters. They also solve the problem with two meta-heuristic algorithms and an efficient local search algorithm. Further, the authors run a post-optimality analysis by conducting a design of experiments using the response surface methodology (RSM). Findings The results of the optimization model reveal that the job rotation schedules and the human cognitive metrics influence the performance of the lean cell. The results of the sensitivity analysis further show that the objective function and the job rotation frequencies are highly sensitive to the other input parameters. Based on the findings from the RSM, the authors derive general rules for the job rotations in a lean cell given the ranges in other input variables. Originality/value The authors integrate the job rotation scheduling model with human behavioral and cognitive parameters and formulate the problem in a lean cell for the first time in the literature. In addition, they use the RSM for the first time in this context and offer a post-optimality analysis that reveals important information about the impact of the job rotations on the performance of operators and the entire working cell.

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Section: Literature Reviewmentioning

confidence: 99%

The job rotation scheduling problem considering human cognitive effects: an integrated approach

Ayough

Farhadi

Zandieh

2021

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“…An improved way was proposed by Kim et al [30] for calculating the imperfect product during long run system. Similarly, a mixed model for single-vendor, along with a single-buyer for defective production process was reformulated by Dey and Giri [31], the effect of learning has a great impact in inspection and was also discussed in this model. Following the same way, Tiwari et al [32] developed a sustainable inventory model with the consideration of carbon emission.…”

Section: Imperfect Production Processmentioning

confidence: 99%

“…Most of the researchers considered imperfect production process or multi-stage production process for imperfect manufacturing system along with manual inspection to detect defective product. Some researchers considered different type of error in inspection or learning effect in inspection [17,18,31] but no one cared about how this inspection error can be removed. In this model, the whole inspection is done automatically by a machine, that is the concept of autonomation policy is utilized to identify the defective items which make an error-free inspection system.…”

Section: Imperfect Production Processmentioning

confidence: 99%

Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?

et al. 2020

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This study explains about a serial smart production system where a single-type of product is produced. This system uses an unequally sized batch policy in subsequent stages. The setup cost is not always deterministic, it can be controllable and reduced by increasing the capital investment cost, and that the production rates in the system may vary within given limits across batches of shipments. Furthermore, as imperfect items are produced in long-run system, to clean the imperfectness autonomation policy is adopted for inspection, which make the process smarter. The shipment lot sizes of the deliveries are unequal and variable. In long-run production system, defective items are produced in “out-of-control” state. In this model, the defect rate is random with a uniform distribution which is clean from the system by autonomation. In addition, in the remanufacturing process, it is assuming that all defective products are repaired, and no defective products are scrapped. The main theme of developing this model is to determine the number of shipments and the optimal production lot size to adjust the production rates and decrease the total system cost under a reduced setup cost by considering the discrete investment and make a serial smart production system. A solution procedure along with an advanced algorithm was proposed for solving the model. Numerical examples with some graphical representations are provided to validate the model.

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“…[17] developed a manufacturing oriented supply chain with inspection errors. [4] developed a learning in inspection in an integrated vendor-buyer model with imperfect production process [2] analyzed a supply chain model with vendor-managed inventory, consignment and quality inspection errors. [20] proposed an integrated production-distribution inventory system involving probabilistic defective and errors in quality inspection under variable setup cost.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated production inventory model with variable production rate on quality of products involving probabilistic defective under variable setup cost

Hemapriya

Uthayakumar

2020

RAIRO-Oper. Res.

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A predetermined production rate in a supply chain model with economic production lot size is quite appropriate for this type of situations as production rate can be changed in some cases to fulfill demand of customers. This paper investigates an integrated production inventory model with variable production rate on quality of products involving probabilistic defective under variable setup cost. As a rate of production has a direct impact on system performance, the production rate is considered as a variable along with the production cost. This production process gone through a long run system as a result after some specific time the production gone out-of-control state due to different issues and produced defective items. In addition, we consider that the defective follows three types of probability distribution function such as, (i) uniform, (ii) triangular and (iii) beta distributions. Two types of lead time crashed concept considering in this model and also we consider three types of continuous probabilistic defective function to find the associated cost of the system. The main objective is to find an optimal solution for an order quantity, safety factor, production cost, setup cost and to analyze how the flexibility of the production rate affects the process quality. An efficient iterative algorithm is designed to obtain the optimal solution of the model numerically and sensitivity analysis table formulate to show the impact of different parameter

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A new approach to deal with learning in inspection in an integrated vendor-buyer model with imperfect production process

Cited by 34 publications

References 41 publications

The job rotation scheduling problem considering human cognitive effects: an integrated approach

The job rotation scheduling problem considering human cognitive effects: an integrated approach

Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?

Integrated production inventory model with variable production rate on quality of products involving probabilistic defective under variable setup cost

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