European J. of Industrial Engineering (24 papers in press)
The impact of online sales in centralized and decentralized dual-channel supply chains
by Subrata Saha
Abstract: This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented.
Keywords: Supply chain management; Dual-channel supply chain; Revenue sharing contract; Pricing strategy; Stackelberg.
Simulation-based Assessment of IoT-Functionality in Perishable Dairy Products
by Raid Al-Aomar, Abdallah Dweekat
Abstract: This paper presents a framework for simulation-based assessment of next-generation IoT-enabled supply chains with a focus on perishable dairy products. The framework integrates real-time data capturing with supply chain modelling and dynamic performance management. The concept of complex event processing (CEP) is utilised to implement IoT functionality. The aim is to reduce waste and losses caused by outdated items, shortages, and inventory discrepancies. The approach is illustrated through a simulation of dairy products perishability in a three-echelon supply chain. Simulation experiments were used to assess the impact of enabling two IoT functionalities; adjusting quantities distributed to retailers based on shelf-life and moving dairy products amongst retailers based on the proximity of their expiration. Simulation results have shown substantial improvement in both economic and operational KPIs of dairy products perishability. Results were also used to trade-off the percentage of expired milk and the inventory fill-rate.
Keywords: simulation modelling; supply chain performance management; internet-of-things; product perishability; dairy products.
Supplier Selection and Order Allocation in the Presence of Suppliers with Exact Annual Capacity
by Ali Ekici, Okan Örsan Özener, Milad Elyasi
Abstract: In this paper, we focus on the supplier selection and order quantity allocation for a single retailer. The retailer orders a product from multiple suppliers with capacities, adds value to the product and fulfils the demand while meeting the minimum quality level. There is a distinct difference between our work and the prior works in the literature in that we assume the (annual) capacities of the suppliers to be exact annual capacities, i.e., the total order amount in a given calendar/fiscal year from a supplier must be less than or equal to its capacity. First, we discuss the implications of this exact annual capacity assumption on the ordering policy of the retailer. Next, to determine an ordering policy, we propose a heuristic algorithm using a novel idea of iteratively updating the annual ordering cost estimates. We demonstrate the efficacy of the proposed algorithm on randomly generated instances. [Submitted: 18 March 2019; Accepted: 22 November 2020]
Keywords: supplier selection; long-run average annual capacity; perfect rate; capacitated suppliers; exact annual capacity.
The effect of transfer lot size on manufacturing lead time: a stochastic analysis
by Clarissa Barco, Moacir Godinho Filho
Abstract: This paper aims to explore, in a quantitative way, the effect of production and transfer lot size on the manufacturing lead time in an environment subject to uncertainties. In order to achieve this objective, a Monte Carlo simulation model is proposed, and several scenarios are analysed, considering six shop-floor variables. The results demonstrate that transfer lot size has little effect on lead time when operating with a manufacturing lot size away from optimal lot size. In order to obtain an excellent performance concerning lead time, it is first necessary to reduce the manufacturing lot size before making efforts to reduce transfer lot size. The results also show that adopting an optimal manufacturing lot size allows the production system to be more stable, allowing shorter lead times. The effect of a supplier manufacturing lot size smaller than optimal lot size on retailer safety stock is disastrous. This result is worse when the desired cycle service level and the demand coefficient of variability are high. [Received: 9 November 2019; Accepted: 28 November 2020]
Keywords: manufacturing lead time; transfer lot; manufacturing lot; safety stocks; uncertainty; Monte Carlo simulation.
An improved Backtracking search algorithm for the flexible job shop rescheduling problem with new job insertions
by Gnanavelbabu Annamalai, Rylan Caldeira
Abstract: In real-world environments, production schedules are subject to several disruptions. Hence it is essential to account for these disruptions while constructing the production schedules. This work considers the flexible job-shop rescheduling problem (FJSRP) considering new job insertions. An improved discrete backtracking search algorithm and a slack-based inserting rescheduling strategy are proposed to address this problem considering makespan as objective. A set of heuristics is used to generate a diverse initial population. An order-preserving crossover and a mutation operator is developed to balance the exploitation and exploration. A transfer criterion is utilised to employ the information of the past population. The algorithms exploitation capability is enhanced by employing a local search technique. Extensive computational work is performed on well-known benchmark instances. Computational results demonstrate the superiority of the proposed approach as well as the rescheduling strategy.
Keywords: backtracking search algorithm; flexible job shop rescheduling problem; job insertion; local search technique; rescheduling strategy.
Solving a Stochastic Programming with Recourse Model for the Stochastic Electric Capacitated Vehicle Routing Problem using a Hybrid Genetic Algorithm
by Elhassania Messaoud
Abstract: This study considers stochastic travel times in an electric capacited vehicle routing problem (ECVRP), where the used electric vehicles may need to visit charging stations due to their battery capacities. The main goal of the present paper is to solve a two-stage stochastic programming with recourse (SPR) model for this problem using a hybrid genetic algorithm (HGA) and a Monte Carlo sampling (MCS) procedure. To show the effectiveness of the proposed approach, the computational experiments are applied to 29 instances with up to 100 customers derived from benchmarks presented in the literature. Firstly the numerical results are compared to those found by CPLEX solver for the deterministic model, thereafter a very large number of scenarios is taken into consideration to evaluate this approach in the stochastic environment using a known probability distribution.
Keywords: transport problem; electric vehicles; capacity constraint; stochastic travel times; stochastic programming with recourse model; genetic algorithm.
An extension of Systematic Layout Planning by using fuzzy AHP and fuzzy VIKOR methods: A case study
by Adolfo Rene Santa Cruz Rodriguez, Paulo Vitor De Oliveira
Abstract: Facility layout problem (FLP) is a complex task generally affected by multiple conflicting criteria, uncertainties, ambiguity, non-commensurable, inaccurate or incomplete information. This paper address these characteristics by extending the systematic layout planning (SLP) procedure with integration of SLP, fuzzy analytic hierarchy process (FAHP) and fuzzy VIKOR (FVIKOR) methods into a fuzzy multi criteria group decision making analysis. The problem is addressed in three stages: 1) feasible layout alternatives are generated using the SLP procedure; 2) the weights of the criteria are determined using FAHP; 3) FVIKOR is used to select the most appropriate layout using qualitative and quantitative criteria. We take advantage of the main characteristic of the FVIKOR method to provide a compromising solution including non-commensurable and conflicting criteria. A real-world case study on improving the layout of a production line in a suction valve industry is conducted to illustrate these approach. The results showed the applicability and effectiveness of the SLP extension to handle FLP under fuzzy environments. [Submitted 6 January 2020; Accepted 12 January 2021]
Keywords: facility layout problem; FLP; fuzzy AHP; FAHP; fuzzy VIKOR; FVIKOR; systematic layout planning; SLP.
OPTIMAL CONTROL OF A MULTI-SUPPLIER AND MULTI-BUYER SUPPLY CHAIN SYSTEM WITH JIT DELIVERY
by Pablo Biswas, Bhaba R. Sarker
Abstract: : A just-in-time centred production-facility supply chain consists of raw material suppliers, manufacturer, and retailers. This paper considers the concept where the production of finished goods follows continuous production cycles. In this scenario, it is assumed that the inventory build-up during production cycles of the concurrent cycle overlap the pure demand consumption cycle to reduce the idle time suggested by previous researchers. Considering this situation, a supply chain inventory models for raw materials, and finished goods supply are developed for multiple suppliers and multiple buyers. In addition, this paper considered that different suppliers deliver the raw materials in instantaneous replenishments supply, and the finished goods are delivered to multiple buyers in a fixed amount after a fixed interval of time (known as just-in-time delivery) according to buyers demand. The problem in this research is formulated as an integer nonlinear programming problem and heuristic solutions are developed to solve it with the help of integer approximations and divide-and-conquer technique. The solution methodologies suggested lead to estimates of optimum production quantity and minimum total system cost. The solutions are verified through numerical examples and illustrated the effectiveness of the method with sensitivity analyses. [Submitted: 27 September 2019; Accepted: 03 January2020]
Keywords: supply chain system; just-in-time delivery; multi-buyer; multi-supplier and single manufacturer.
CONWIP pull system designs for bicycle chain manufacturing
by Taho Yang, Yu-Hsiu Hung, Guan-Cheng Huang
Abstract: The bicycle chain is an important component of a bicycle and is generally produced by a batch manufacturing process while incurs a large work-in-process (WIP) and a prolonged production lead time. The present study examines the feasibility of using an alternative constant work-in-process (CONWIP) pull system design for the chain manufacturing process. Five different design alternatives are proposed. For each alternative, the associated design variables are determined via simulation optimization. In addition, a practical case study is employed for empirical illustration purposes. The simulation results show that the proposed CONWIP designs reduce the WIP level and production lead time by an average of 56% and 37%, respectively. In other words, the CONWIP methodology provides a promising approach for solving the bicycle chain manufacturing system design problem in real-world companies. The proposed CONWIP design methodology can also be applied to any multi-stage manufacturing line.
Keywords: Bicycle chain manufacturing; constant work-in-process (CONWIP); pull production; simulation optimization.
A decision-support model for dock and transport management after inbound logistics disruptions in the automotive sector
by Mohammadtaghi Falsafi, Davide Masera, Julien Mascolo, Rosanna Fornasiero
Abstract: One of the major disruptions in automotive supply chain is related to the on-time arrival of components from suppliers to assembly plants. In this paper, we develop an operative decision-support model to avoid ripple effect of these disruptions on production scheduling. In particular, based on strategies for truck-dock re-assignment and transport mode selection, the model is applied to a case study at Fiat Chrysler Automobiles (FCA). Moreover, the paper elaborates on the resilience and robustness of the supply chain in dealing with vulnerabilities in different phases of decision-making. The model allows supply chain managers to efficiently organise the transport modes of delayed orders, the in-plant material handling equipment, the arrival of trucks in the parking lot, and the use of inbound docks. [Submitted: 10 January 2021; Accepted: 5 April 2021]
Keywords: disruption management; automotive sector; inbound logistics; dock management; transport management; supply chain resilience; truck-dock rescheduling; mixed-integer linear programming; MILP.
Order acceptance and scheduling problem with outsourcing in seru production system considering lot-spitting
by Lili Wang, Zhe Zhang, Yong Yin
Abstract: This paper focuses on the order acceptance and scheduling problem considering lot-spitting with outsourcing decisions simultaneously in seru production system. Assume that the companys production capacity is limited, and that the outsourcer will require different outsourcing costs for different orders. Therefore, when the outsourcing cost of an order is relatively high, the company can choose to process it internally or reject the order directly, so that the company can achieve higher revenue. To solve this complex problem, a mixed 0
Keywords: order acceptance and scheduling; OAS; seru; outsourcing; lot-spitting; hybrid intelligent algorithm.
Heuristic Procedure for Bi-capacitated Multiple-trip Vehicle Routing Problem
by Tarit Rattanamanee, Suebsak Nanthavanij
Abstract: The multiple-trip vehicle routing problem with physical workload (MTVRP-WL) or bi-capacitated MTVRP is intended to find an optimal number of delivery trucks and their travel routes to serve a set of customers having constant load demands within a given time limit. Delivery workers who are pre-assigned to trucks must manually unload goods at customer locations. Both trucks and workers are heterogeneous in terms of the load capacity and working energy capacity, respectively. Initially, the random nearest neighbourhood search technique is employed to generate an initial feasible solution. Then, the solution is improved using two local search operators, namely, greedy swap and 2-opt. The improvement algorithms are repeated for a number of iterations until no further improvement is obtained. From a computation experiment, the heuristic procedure is found to be efficient since it can obtain near-optimal MTVRP solutions in reasonable computation time. [Submitted: 5 November 2020; Accepted: 7 April 2021]
Keywords: multiple-trip vehicle routing problem; bi-capacitated problem; heuristic algorithm; local search; physical workload; intra-city logistics.
Supply chain optimal ordering policy under two-level trade credit with default risk
by Chengfeng Wu, Qiuhong Zhao, Chunfeng Xu
Abstract: The paper assumes that the manufacturer offers the wholesaler trade credit, and the wholesaler provides the retailer with trade credit in a three-echelon supply chain. First, we formulate the mathematical models that include the time value of capital and the partial default risk for the three members, respectively. Second, we derive the existence and uniqueness conditions of the optimal lot-size or production quantity for the members under decentralised replenishment policy. Finally, we present the sensitivity analysis of the optimal solution with respect to the parameters to provide managerial insights. The results show that the larger standard deviation of the demand, the more effective trade credit as the settlement method. The key contribution of the paper is that we present an ordering model that optimises lot sizes with two-level trade credit and investigate the transmission effect of default credit risk in a three-echelon supply chain under an uncertain market environment. [Submitted: 23 September 2020; Accepted: 8 April 2021]
Keywords: supply chain; two-level trade credit; default risk; newsvendor model.
Joint ordering policy for a conditional trade credit model with two retailers
by Zhen Zhang, Song-Tao Zhang, Ming-Shi Yue
Abstract: This paper focuses on the cooperation mechanism between two retailers. To reduce the average processing cost, the supplier usually sets a threshold for trade credit to stimulate retailers orders. Retailers can enjoy permissible delay in payments only when their order quantities are more than or equal to the given threshold. However, considering the diversity of retailers, the motivation effect of the threshold is limited. To resolve the problem, the supplier can additionally provide its retailers with a joint-ordering policy under which they can make delayed payments as long as their total order quantity meets the required threshold. We provide a mutually acceptable order-allocation scheme for two retailers, and determine the optimal payment methods for them. In addition, an optimal threshold is identified for the supplier to maximise the total order quantity of retailers. Based on this, some managerial insights are obtained. [Submitted 27 February 2020; Accepted 8 April 2021]
Keywords: inventory; economic order quantity; EOQ; supply chain management; conditional trade credit; joint-ordering policy; cooperation mechanism; non-cooperative game; tacit bargaining.
Synthetic control chart with curtailment for monitoring shifts in fraction nonconforming
by Salah Haridy, Nger Ling Chong, Michael Khoo, M. Shamsuzzaman, Philippe Castagliola
Abstract: The integration of the curtailment method with control charts considerably improves the detection speed by signalling an out-of-control condition prior to the inspection of the whole sample. To date, few research works have focused on the incorporation of the curtailment method to improve the performance of control charts. Thus, this paper incorporates the curtailment approach with the synthetic chart to propose a synthetic with curtailment (Curt_Syn) control chart for detecting upward shifts in the fraction non-conforming, p. We compare the newly developed Curt_Syn chart with the synthetic, exponentially weighted moving average (EWMA), cumulative sum (CUSUM), EWMA with curtailment (Curt_EWMA), and CUSUM with curtailment (Curt_CUSUM) charts. From an overall perspective, the results reveal that the Curt_Syn chart surpasses the synthetic chart by 38% under various conditions. For all p shifts, the Curt_Syn chart outperforms the CUSUM and EWMA charts. When the p shift is large, the Curt_Syn chart is superior to the Curt_CUSUM and Curt_EWMA charts. To demonstrate the implementation of the Curt_Syn chart, an illustrative example is provided. [Received: 30 April 2019; Accepted: 7 April 2021]
Keywords: control chart; synthetic chart; curtailment; fraction non-conforming; quality control; statistical process control; SPC; monitoring; attribute chart.
Waiting time distribution in single-channel deterministic flow lines with discrete interarrival time distributions
by Woo-Sung Kim, Kyungsu Park
Abstract: Although previous studies proved that deterministic flow lines can be analysed separately by an exact decomposition method called a channel method and that the delay an item experiences in each machine possesses a Markovian property, the exact performance measures for the system with general arrival process cannot be obtained due to the lack of the results on relevant GI/D/1 queue. The solution obtained only for the system with specific arrival patterns such as geometric distribution or JIT arrivals considering setups. In this paper, exact decomposition methods are investigated through the systems consisting of one channel. Assuming general and discrete inter-arrival times, we introduce a procedure to calculate the equilibrium probabilities for waiting time distributions. It is demonstrated that probabilities can be computed by a matrix analytic method and recursions based on the decomposition methods. Inspired by the steel product manufacturing process, two-stage conveyor belt systems are analysed as an application. [Received: 28 July 2020; Accepted: 1 March 2021]
Keywords: flow line model; stochastic modelling; Markov chain model; steel manufacturing system; tandem queue.
Optimization of a sustainable fuzzy EPQ inventory model using sextic equation
by Ganesan Subburaj, R. Uthayakumar
Abstract: We develop a fuzzy EPQ inventory model to achieve sustainability and profit maximisation. Cost measures are included at every stage of the production and inventory process to handle carbon emissions safely. Fuzzy number representation of the input parameters helps to accommodate uncertainties in the inventory decision-making process. The fuzzy net profit functions ambiguity level determines the degree of uncertainty in the net profit. Descartes rule of signs is used in a sextic equation to establish a solution to the optimal length of the production run. The numerical results show that increasing ambiguity in the fuzzy profit function will decrease the net profit. Accuracy in predicting production cost, setup cost, and annual demand is essential as the net profit is more sensitive to these parameters. A multivariate regression equation is fitted to estimate a possible crisp net profit from the corresponding fuzzy net profit for given demand and production rates.
Keywords: sustainability; EPQ inventory; trapezoidal fuzzy number; Descartes rule of signs.
An Economic Order Quantity Model for Pareto Distribution Deterioration with Linear Demand under Linearly Time-Dependent Shortages
by Sindhuja. S, P. Arathi
Abstract: The inventory models for deteriorating items aim to reduce the total cost under normal market conditions. This paper focuses on the possible effects of minimising total cost by developing an economic order quantity (EOQ) model, where the deterioration is considered as Pareto distribution with linear demand. This model is applicable for vegetable vendors to make inventory decisions in the inventory system under the influence of optimal values. The linear demand and shortage of cost are also taken into consideration. To illustrate the proposed EOQ model, numerical examples and corresponding sensitivity analysis on the parameters A, c, d, pc, h, s, ? and ? are discussed and compared with the existing models. The result of the model developed in this paper is based on the deterioration leading to significant effects of the Pareto distribution deterioration variables ? and ? on the
Keywords: economic order quantity; EOQ; Pareto distribution; deterioration; linear demand; shortage.
Solving an Integrated Mathematical Model for Crew Pairing and Rostering Problems by an Ant Colony Optimization Algorithm
by Saeed Saemi, Alireza Rashidi Komijan, Reza Tavakkoli-Moghaddam, Mohammad Fallah
Abstract: The crew pairing problem (CPP) and the crew rostering problem (CRP) are two sub-problems of a crew scheduling problem (CSP). Solving these problems based on a sequential approach may not yield the optimum solution. Therefore, the present study aims to consider the integrated crew pairing and crew rostering problem and present a new mathematical formulation. Due to its NP-Hardness complexity, a meta-heuristic algorithm based on ant colony optimisation (ACO) is designed and used to solve the integrated problem and sequential approach (CRP followed by CPP) in some test problems extracted from a data set. The solutions provided by ACO for the integrated problem show 21.64% cost reduction in a reasonable time increase in comparison with those obtained by the sequential approach. Also, the ACO algorithm can provide solutions with a 2.96% average gap to the optimal solutions (by the exact method) for small-sized problems. Also, the proposed integrated approach leads to solutions with the best/optimal number of crew members to be assigned. The findings indicate that the proposed ACO has an efficient performance in solving the integrated problem.
Keywords: crew pairing and crew rostering; crew scheduling; inseparable flights; ant colony optimisation; ACO.
An original approach to assess robustness of Road Freight Transport plannings based on a Dynamic Risk Identification
by Antoine CLEMENT, Didier Gourc, Daouda Kamissoko, François Marmier
Abstract: The road freight transport sector contributes significantly to the delivery of goods. Today, more than 90% of goods are conveyed using the road transport mode. In the same time, customers requirements become more and more numerous and accurate, which increases the complexity of planner work. The aim of this work is to propose to planners robustness indicators measuring the chance the planned tour could respect the requirements. Based on a planning system giving several feasible daily schedules, our approach allows to dynamically identify the risks that could impact each planning and then simulate the influence of those risks on the plans activities to assess robustness indicators. They are composed of an indicator measuring the probability to respect the customers requirements and two actionable data. These actionable data give to planners information on levers he could use to increase the robustness of the plan. [Submitted: 11 September 2020; Accepted: 27 April 2021]
Keywords: risk identification; robustness; decision making; danger; daily schedule; road freight transport.
New approach for quality function deployment with an extended alternative queuing method under linguistic Pythagorean fuzzy environment
by Ye-Jia Ping, Ran LIu, Ze-Ling Wang, Hu Chen Liu
Abstract: As a customer-driven tool to support the development of new products or services, quality function deployment (QFD) is able to transform customer requirements (CRs) into suitable engineering characteristics (ECs) to maximise the customer satisfaction. However, the conventional QFD method has some weaknesses limiting its effectiveness in the real applications. In this study, a new QFD approach based on linguistic Pythagorean fuzzy sets (LPFSs) and alternative queuing method (AQM) is constructed to enhance the performance of the traditional QFD. First, we express the assessments from experts on the relationships between CRs and ECs using the LPFSs. Second, we apply an extended AQM to determine the importance prioritisation of ECs. Additionally, a consensus reaching algorithm is adopted to dynamically determine the relative weights of experts considering their inconsistent judgements. An illustrative application of 5G smartphone development is conducted to demonstrate the feasibility and ef?ciency of our proposed QFD approach. Through the empirical case with a comparative analysis, the proposed approach is proved to be useful and practical for capturing experts opinions and prioritising ECs in QFD. [Submitted: 19 March 2020; Accepted: 11 April 2021]
Keywords: quality function deployment; QFD; linguistic Pythagorean fuzzy set; LPFS; alternative queuing method; AQM; consensus reaching method; product development.
Inventory control for the closed-loop supply chain with technological progress and planned shortages
by Shih-Pin Chen, Yu-Ming Lin
Abstract: The impact of Industry 4.0 has received much attention in academic and practice fields. Therefore, understanding the effects of technological progress in production on closed-loop supply chain (CLSC) inventory management is critical. In view of profit efficiency, this paper investigates the effects of technological progress in production on inventory policies in a CLSC considering planned shortages. A CLSC production-inventory model is proposed to jointly determine sale and collection prices and production time points. The representative numerical results show that technological progress in manufacturing inconsistently has a positive impact on the NPU because the total quantity produced and cycle length vary. The impact of technological progress may be greater in the manufacturing process than in the remanufacturing process. The results can aid production managers in finding optimal production-inventory strategies considering technological progress and planned shortages. Additionally, the results provide useful information regarding the impact of technological progress in selecting investment targets. [Received: 5 August 2020; Accepted: 16 March 2021]
Keywords: inventory; technological progress; remanufacturing; sequential quadratic programming; supply chain management; learning effects.
Scenario-based stochastic shelter location-allocation problem with vulnerabilities for disaster relief network design
by Sweety Hansuwa, Usha Mohan, Viswanath Kumar Ganesan
Abstract: We formulate the shelter location-allocation problem considering the vulnerability of the demand locations and their network connectivities with the shelter locations for disaster managements preparedness and response phase. We propose a scenario-based stochastic model that assigns the set of candidate locations evaluating operational, budgetary limitations, and service level expectations. The solution presents an evacuee-allocation plan considering the best collection of less vulnerable network connectivities between the demand areas and the shelter locations. We present a linear relaxation heuristic and compare the heuristic performance with the scenario-based formulation solved using CPLEX 12.8 optimisation solver for various problem sizes. We finally apply and solve the problem using real-life case data obtained during the major flooding event in and around the Chennai Metropolitan Development Area during 2015 to present our models applicability and emergency response requirements. [Submitted: 12 November 2020; Accepted: 19 April 2021]
Keywords: disaster management; shelter location-allocation; stochastic programming; linear relaxation heuristic.
A Mathematical Model for the Optimal Robust Design of Cause Selecting Control Charts
by Ahmed M. Ghaithan, SALIH OSMAN Duffuaa, Ahmed M. Attia
Abstract: Cause selecting charts (CSC) are statistical control-charts for monitoring multiple sequential processes; in contrast, Shewhart control-charts are useful for monitoring independent processes. The economic-statistical design of CSC involves the selection of the optimal design parameters that include the width of the chart, sample size, and sampling interval. The application of economic-statistical criteria is a well-established and active research field. However, these design approaches may not be reliable for a dynamic production environment due to the uncertainty associated with the values of the model parameters. The purpose of this paper is to develop a robust economic-statistical model for the design of CSC. The model is intended to minimise the risk associated with the incidence of different scenarios in a real production environment. Through the use of examples and sensitivity analysis, it is demonstrated that the model provides design parameters that are more sensitive to shifts, protect against the occurrence of other scenarios, and results in charts with a higher power.
Keywords: quality; cause selecting chart; CSC; control charts; robust design; dependent processes.