Supply Chain Coordination in 2-Stage-Ordering-Production System with Update of Demand Information

Kusukawa, Etsuko Korean Institute of Industrial Engineers 2014 Industrial Engineeering & Management Systems Vol.13 No.3

It is necessary for a retailer to improve responsiveness to uncertain customer demand in product sales. In order to solve this problem, this paper discusses an optimal operation for a 2-stage-ordering-production system consisting of a retailer and a manufacturer. First, based on the demand information estimated at first order time $t_1$, the retailer determines the optimal initial order quantity $Q^*_1$, the optimal advertising cost $a^*_1$ and the optimal retail price $p^*_1$ of a single product at $t_1$, and then the manufacturer produces $Q^*_1$. Next, the retailer updates the demand information at second order time $t_2$. If the retailer finds that $Q^*_1$ dissatisfies the demand indicated by the demand information updated at $t_2$, the retailer determines the optimal second order quantity $Q^*_2$ under $Q^*_1$ and adjusts optimally the advertising cost and the retail price to $a^*_2$ and $p^*_2$ at $t_2$. Here, decision-making approaches for two situations are made-a decentralized supply chain (DSC) whose objective is to maximize the retailer's profit and an integrated supply chain (ISC) whose objective is to maximize the whole system's profit. In the numerical analysis, the results of the optimal decisions under DSC are compared with those under ISC. In addition, supply chain coordination is discussed to adjust the unit wholesale price at each order time as Nash Bargaining solutions.

A Synthetic Exponentially Weighted Movingaverage Chart for High-yield Processes

Etsuko Kusukawa,Takayuki Kotani,Hiroshi Ohta 대한산업공학회 2008 Industrial Engineeering & Management Systems Vol.7 No.2

As charts to monitor the process fraction defectives, P, in the high-yield processes, Mishima et al. (2002) discussed a synthetic chart, the Synthetic CS chart, which integrates the CS (Confirmation Sample) CCC(Cumulative Count of Conforming)-r chart and the CCC-r chart. The Synthetic CS chart is designed to monitor quality characteristics in real-time. Recently, Kotani et al. (2005) presented the EWMA (Exponentially Weighted Moving-Average)CCC-r chart, which considers combining the quality characteristics monitored in the past with one monitored in real-time. In this paper, we present an alternative chart that is more superior to the EWMACCC-r chart. It is an integration of the EWMACCC-r chart and the CCC-r chart. In using the proposed chart, the quality characteristic is initially judged as either the in-control state or the out-of-control state, using the lower and upper control limits of the EWMACCC-r chart. If the process is not judged as the in-control state by the EWMACCC-r chart, the process is successively judged, using the CCC-r chart to confirm the judgement of the EWMACCC-r chart. We compare the ANOS (Average Number of Observations to Signal) of the proposed chart with those of the EWMACCC-r chart and the Synthetic CS chart. From the numerical experiments, with the small size of inspection items, the proposed chart is the most sensitive to detect especially the small shifts in P among other charts.

CS<SUB>¯X</SUB>Chart for a Small Number of Subgroups

Etsuko Kusukawa,Hiroshi Ohta 대한산업공학회 2003 Industrial Engineeering & Management Systems Vol.2 No.2

A Synthetic Chart to Monitor The Defect Rate for High-Yield Processes

Kusukawa, Etsuko,Ohta, Hiroshi Korean Institute of Industrial Engineers 2005 Industrial Engineeering & Management Systems Vol.4 No.2

Kusukawa and Ohta presented the $CS_{CQ-r}$ chart to monitor the process defect $rate{\lambda}$ in high-yield processes that is derived from the count of defects. The $CS_{CQ-r}$ chart is more sensitive to $monitor{\lambda}$ than the CQ (Cumulative Quantity) chart proposed by Chan et al.. As a more superior chart in high-yield processes, we propose a Synthetic chart that is the integration of the CQ_-r chart and the $CS_{CQ-r}$chart. The quality characteristic of both charts is the number of units y required to observe r $({\geq}2)$ defects. It is assumed that this quantity is an Erlang random variable from the property that the quality characteristic of the CQ chart follows the exponential distribution. In use of the proposed Synthetic chart, the process is initially judged as either in-control or out-of-control by using the $CS_{CQ-r}$chart. If the process was not judged as in-control by the $CS_{CQ-r}$chart, the process is successively judged by using the $CQ_{-r}$chart to confirm the judgment of the $CS_{CQ-r}$chart. Through comparisons of ARL (Average Run Length), the proposed Synthetic chart is more superior to monitor the process defect rate in high-yield processes to the stand-alone $CS_{CQ-r}$ chart.

A Synthetic Chart to Monitor The Defect Rate for High-Yield Processes

Etsuko Kusukawa,Hiroshi Ohta 대한산업공학회 2005 Industrial Engineeering & Management Systems Vol.4 No.2

Supply Chain Coordination in 2-Stage-Ordering-Production System with Update of Demand Information

Etsuko Kusukawa 대한산업공학회 2014 Industrial Engineeering & Management Systems Vol.13 No.3

It is necessary for a retailer to improve responsiveness to uncertain customer demand in product sales. In order to solve this problem, this paper discusses an optimal operation for a 2-stage-ordering-production system consisting of a retailer and a manufacturer. First, based on the demand information estimated at first order time t₁, the retailer determines the optimal initial order quantity Q₁<SUP>*</SUP> , the optimal advertising cost a₁<SUP>*</SUP> and the optimal retail price p₁<SUP>*</SUP> of a single product at t₁ , and then the manufacturer produces Q₁<SUP>*</SUP> . Next, the retailer updates the demand information at second order time t₂ . If the retailer finds that Q₁<SUP>*</SUP> dissatisfies the demand indicated by the demand information updated at t₂ , the retailer determines the optimal second order quantity Q₂<SUP>*</SUP> under Q₁<SUP>*</SUP> and adjusts optimally the advertising cost and the retail price to a₂<SUP>*</SUP> and p₂<SUP>*</SUP> at t₂ . Here, decision-making approaches for two situations are made?a decentralized supply chain (DSC) whose objective is to maximize the retailer’s profit and an integrated supply chain (ISC) whose objective is to maximize the whole system’s profit. In the numerical analysis, the results of the optimal decisions under DSC are compared with those under ISC. In addition, supply chain coordination is discussed to adjust the unit wholesale price at each order time as Nash Bargaining solutions.

Optimal Operation for Green Supply Chain with Quality of Recyclable Parts and Contract for Recycling Activity

Etsuko Kusukawa,Sho Alozawa 대한산업공학회 2015 Industrial Engineeering & Management Systems Vol.14 No.3

This study discusses a contract to promote collection and recycling of used products in a green supply chain (GSC). A collection incentive contract is combined with a reward-penalty contract. The collection incentive contract for used products is made between a retailer and a manufacturer. The reward-penalty contract for recycling used products is made between a manufacturer and an external institution. A retailer pays an incentive for collecting used products from customers and delivers them to a manufacturer with a product order quantity under uncertainty in product demand. A manufacturer remanufactures products using recyclable parts with acceptable quality levels and covers a part of the retailer’s incentive from the recycled parts by sharing the reward from an external institution. Product demand information is assumed as (i) the distribution is known (ii) mean and variance are known. Besides, the optimal decisions for product quantity, collection incentive of used products and lower limit of quality level for recyclable parts under decentralized integrated GSCs. The analysis numerically investigates how (1) contract for recycling activity, (ii) product demand information and (iii) quality of recyclable parts affect the optimal operation for each GSC. Supply chain coordination to shift IGSC is discussed by adopting Nash Bargaining solution.

Optimal Operation for Green Supply Chain with Quality of Recyclable Parts and Contract for Recycling Activity

Kusukawa, Etsuko,Alozawa, Sho Korean Institute of Industrial Engineers 2015 Industrial Engineeering & Management Systems Vol.14 No.3

This study discusses a contract to promote collection and recycling of used products in a green supply chain (GSC). A collection incentive contract is combined with a reward-penalty contract. The collection incentive contract for used products is made between a retailer and a manufacturer. The reward-penalty contract for recycling used products is made between a manufacturer and an external institution. A retailer pays an incentive for collecting used products from customers and delivers them to a manufacturer with a product order quantity under uncertainty in product demand. A manufacturer remanufactures products using recyclable parts with acceptable quality levels and covers a part of the retailer's incentive from the recycled parts by sharing the reward from an external institution. Product demand information is assumed as (i) the distribution is known (ii) mean and variance are known. Besides, the optimal decisions for product quantity, collection incentive of used products and lower limit of quality level for recyclable parts under decentralized integrated GSCs. The analysis numerically investigates how (1) contract for recycling activity, (ii) product demand information and (iii) quality of recyclable parts affect the optimal operation for each GSC. Supply chain coordination to shift IGSC is discussed by adopting Nash Bargaining solution.

A Synthetic Exponentially Weighted Moving-average Chart for High-yield Processes

Kusukawa, Etsuko,Kotani, Takayuki,Ohta, Hiroshi Korean Institute of Industrial Engineers 2008 Industrial Engineeering & Management Systems Vol.7 No.2

As charts to monitor the process fraction defectives, P, in the high-yield processes, Mishima et al. (2002) discussed a synthetic chart, the Synthetic CS chart, which integrates the CS (Confirmation Sample)$_{CCC(\text{Cumulative Count of Conforming})-r}$ chart and the CCC-r chart. The Synthetic CS chart is designed to monitor quality characteristics in real-time. Recently, Kotani et al. (2005) presented the EWMA (Exponentially Weighted Moving-Average)$_{CCC-r}$ chart, which considers combining the quality characteristics monitored in the past with one monitored in real-time. In this paper, we present an alternative chart that is more superior to the $EWMA_{CCC-r}$ chart. It is an integration of the $EWMA_{CCC-r}$ chart and the CCC-r chart. In using the proposed chart, the quality characteristic is initially judged as either the in-control state or the out-of-control state, using the lower and upper control limits of the $EWMA_{CCC-r}$ chart. If the process is not judged as the in-control state by the $EWMA_{CCC-r}$ chart, the process is successively judged, using the <CCC-r chart to confirm the judgement of the $EWMA_{CCC-r}$ chart. We compare the ANOS (Average Number of Observations to Signal) of the proposed chart with those of the $EWMA_{CCC-r}$ chart and the Synthetic CS chart. From the numerical experiments, with the small size of inspection items, the proposed chart is the most sensitive to detect especially the small shifts in P among other charts.

CSX Chart for A Small Number of Subgroups

Etsuko Kusukawa,Hiroshi Ohta 대한산업공학회 2003 Industrial Engineeering & Management Systems Vol.2 No.2

Steiner has presented a CS (Confirmation Sample)chart to detect more sensitively small ormoderate shifts in the process mean from the in-control state on the Shewhartchart. In the case that in-control values for the process mean and variance,and, are unknown, these unknown parameter values are estimated from some m initial subgroups of size n taken when the process is believed to be stable. When the centerline and control limits of thechart are set up by using these estimated parameters, the actual values of type I error of thechart does not match the specified value of it. Recently, Nedumaran and Pignatiello have presented an approach for constructing control limits of thechart when those control limits are estimated using data from a small number of subgroups, based on the run length distribution. In this paperwe construct a modifiedchart for a small number of subgroups, based on the approach proposed by Nedumaran and Pignatiello. The performance of the proposed chart was compared with those of the usual chart and the modifiedchart constructed by Nedumaran and Pignatiello through the computer simulations.