Multi-Item Production Planning and Management System Based on Unfulfilled Order Rate in Supply Chain

Ueno, Nobuyuki; Okuhara, Koji; Ishii, Hiroaki; Shibuki, Hiroaki; Kuramoto, Toshiaki

doi:10.15807/jorsj.50.201

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…To take the randomness of defective rate x into account, by applying the expected values of x in the cost analysis and substituting all variables from equations (1) to (9) in Eq. ( 10), the following expected E[TCU(Q)] can be obtained:…”

Section: Description and Mathematical Modellingmentioning

confidence: 99%

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Multi-Item EPQ Model with Scrap, Rework and Multi-Delivery using Common Cycle Policy

Chiu¹,

Tseng

et al. 2014

Journal of Applied Research and Technology

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This paper is concerned with determining the optimal common production cycle policy for a multi-item economic production quantity (EPQ) model with scrap, rework and multiple deliveries. The classic EPQ model considers the optimal replenishment quantity of single product under a perfect production assumption and a continuous inventory issuing policy. However, in real life production planning, manufacturing firms often plan to have multiple products made in turn on a single machine in order to maximize the machine utilization. Also, dealing with random defective items during the production run seems to be an inevitable task, and the multi-delivery policy is commonly adopted for distributing finished items to customers. In this study, we assume a portion of nonconforming items is scrap and the other portion of them can be reworked and repaired in the same production cycle with additional cost. The objective is to determine an optimal common production cycle time that minimizes the long-run average cost per unit time for such a specific multi-item EPQ model with scrap, rework and multi-delivery policy. Mathematical modeling and analysis is used and a closed-form optimal common cycle time for multi-item production planning is obtained. A numerical example is provided to demonstrate the practical usage of research result.

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Section: Description and Mathematical Modellingmentioning

confidence: 99%

“…Both methods were compared with a cyclic production strategy. Studies related to various aspects of multi-item production planning and optimization issues have since been extensively conducted [6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Multi-Item EPQ Model with Scrap, Rework and Multi-Delivery using Common Cycle Policy

Chiu¹,

Tseng

et al. 2014

Journal of Applied Research and Technology

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“…Therefore, to the best of our knowledge, no study has been conducted to identify the variability characteristics of ADI systems and solve possible problems. Ueno et al (2007) proposed a multi-item production and inventory planning method for mass customization, considering the restrictions of daily manufacturing capacity. Ueno (2018) also conducted a study to clarify the causes of the bullwhip effect and to quantify it from the ordering behavior based on the uncertain demand in a production system in a two-stage supply chain using ADI.…”

Section: Introductionmentioning

confidence: 99%

Modeling and analyzing a simple multi-stage supply chain using advance demand information

Aoki

TSUMAYA

2022

JAMDSM

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In a production system using advance demand information, the advance demand information is sent to an upstream company a certain period of time before production, and the firm-order information is sent just before production. Unfortunately, upstream companies are frequently burdened with excess inventory and late deliveries. Therefore, it is necessary to analyze the effect of the variable factors, such as demand fluctuation and the gap between the advance demand information and the firm-order information. The model was based on the following three steps. First, considering a supply chain consisting of four companies, suppliers can be classified into three types, according to the timing of the firm order and production. Second, the supply chain consists of a combination of three types of suppliers, depending on the timing of the sending firm order. Finally, the production-activity structure for each type of supplier was modeled. Then, they were formulated and implemented as an analysis simulator. Using this simulator, several case studies were investigated. As a result, it was confirmed that the bullwhip effect was increased by the sudden fluctuation of demand, especially when the demand increased. In addition, the supplier whose daily production numbers and stock quantity fluctuated was drastically changed by the gap between the advance demand information and the firm order was identified.

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“…Through numerical illustrations authors showed that their non-stationary approach could outperform the stationary heuristic. Ueno et al (2007) addressed a common problem in meeting mass diversity customization needs in the automobile industry. Authors presented a multi-product fabrication planning approach to deal with the problem of mass customization needs under daily production capacity constraint.…”

Section: Introductionmentioning

confidence: 99%

Determining rotation cycle and distribution frequency for a vendor-buyer integrated multi-item system considering an external provider and rework

Chiu¹,

Chen²,

Chang³

et al. 2019

10.5267/j.ijiec

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Transnational corporations, which operate in competitive global marketplaces, have to build the best possible intra-supply chain model for meeting, on time, clients' need for multiple products with the requisite quality. Since fabrication capacity is always limited, the introduction of the external provider option can assist in leveling utilization, smoothing manufacturing schedules, eliminating overtime usage, and shortening the length of the fabrication cycle. Seeking to support intra-supply chain planning, this research aims to provide a concurrent decision on rotation cycle length and delivery frequency for a multi-item vendor-buyer incorporated type of intra-supply chain system with an external provider and rework. First, a model is built to represent this hybrid inventory replenishing problem. Then, renewal reward theory, mathematical derivation, and Hessian matrix equations are utilized to arrive at the expected total cost of the model, as well as the best policies for both cycle time and distribution. Last, the applicability and sensitivity analyses of our results are exhibited by a numerical demonstration. The insights obtained from this study about critical system-related information, such as the individual and joint impacts of the variation in outsourcing and reworking-related features on the system's optimal operating policy and various performance parameters, will offer crucial help to the managerial functions of planning and decision making in firms using this realistic multi-item hybrid intra-supply chain system.

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Multi-Item Production Planning and Management System Based on Unfulfilled Order Rate in Supply Chain

Cited by 8 publications

References 3 publications

Multi-Item EPQ Model with Scrap, Rework and Multi-Delivery using Common Cycle Policy

Multi-Item EPQ Model with Scrap, Rework and Multi-Delivery using Common Cycle Policy

Modeling and analyzing a simple multi-stage supply chain using advance demand information

Determining rotation cycle and distribution frequency for a vendor-buyer integrated multi-item system considering an external provider and rework

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