Closed-loop supply chain configuration for new and reconditioned products: An integrated optimization model

Closed-Loop Supply Chain Management (CLSCM) is considered as a strategic response to the call for corporate sustainability while further expanding the scope of value creation to include product reconstruction. The Closed-Loop Supply Chain (CLSC) performance is directly related to the CLSC network design. The CLSC network design, with long-term and strategic connotations, involves selection of an integrated network of partner organizations to be engaged on one hand in the forward supply chain processes relevant to families of existing and new products and also involved in reverse supply chain activities relevant to reconstruction of the returned products. At the tactical level, Closed-Loop Supply Chain Configuration (CLSCC) attempts to address issues pertinent to launch of a new product and its reconstruction. The CLSC network design is well studied in the current literature, but addressing the CLSCC is neglected. To study the CLSCC problem we: (a) develop an integrated optimization model for problem; (b) present a real-world case study of a battery manufacturer; (c) based on the case study, we conduct a comprehensive set of computational experiments followed by a series of what-if analyses to compare profitability of the Forward Supply Chain Configuration (FSCC) versus the CLSCC; and (c) discuss the key observations and managerial implications drawn from the computational experiments, applicable to other real-world instances. The significant outcomes of the study suggest that: (i) performance of the firm׳s base case integrated CLSCC model is significantly better than the current supply chain model (ii) the sales-price ratio of new battery is found to be negatively related with the maximum acquiring price of used batteries; (iii) combination of sales price ratios of new and reconditioned batteries determines the total net profit for a given return rate. Finally, important managerial insights and scope for future research are discussed.     

Coordinating pricing and production decisions for multiple products

We consider a dynamic problem of joint pricing and production decisions for a profit-maximizing firm that produces multiple products. We model the problem as a mixed integer nonlinear program, incorporating capacity constraints, setup costs, and dynamic demand. We assume demand functions to be convex, continuous, differentiable, and strictly decreasing in price. We present a solution approach which is more general than previous approaches that require the assumption of a specific demand function. Using real-world data from a manufacturer, we study problem instances for different demand scenarios and capacities and solve for optimal prices and production plans. We present analytical results that provide managerial insights on how the optimal prices change for different production plans and capacities. We extend some of the earlier works that consider single product problems to the case of multiple products and time variant production capacities. We also benchmark performance of proposed algorithm with a commercial solver and show that it outperforms the solver both in terms of solution quality and computational times.     

Causal Linkages in Supply Chain Management: An Exploratory Study of North American Manufacturing Firms

In this paper we investigate the key causal linkages in supply chain management. We propose a conceptual framework and test this framework on data from 215 North American manufacturing firms using structural equation modeling techniques. Three major research issues are addressed in this study: Do sourcing decisions affect the degree to which firms achieve manufacturing goals of cost, flexibility, dependability, and quality? Does the degree of manufacturing goal achievement lead to higher customer responsiveness? Does the degree of manufacturing goal achievement lead to higher internal manufacturing performance? The study examines the relationship among sourcing decisions, manufacturing goals, customer responsiveness, and manufacturing performance. The results support the notion that an integrated supply chain involves aligning sourcing decisions to achieve manufacturing goals that are set to respond favorably to the needs of customers.     

Effective Design of Products/Services: An Approach Based on Integration of Marketing and Operations Management Decisions*

This paper presents an integrated framework for designing profit‐maximizing products/ services, which can also be produced at reasonable operating difficulty levels. Operating difficulty is represented as a function of product and process attributes, and measures a firm's relative ease or difficulty in meeting customer demand patterns under specified operating conditions. Earlier optimum product design procedures have not considered. operational difficulty. We show that optimum profit, market share, cost, and product profiles are dependent on operating difficulty level. Empirical results from the pizza delivery industry demonstrate the value of the proposed Effective Product/Service Design approach.     

A stochastic programming model for production planning of perishable products with postponement

This study addresses the production planning problem for perishable products, in which the cost and shortage of products are minimised subject to a set of constraints such as warehouse space, labour working time and machine time. Using the concept of postponement, the production process for perishable products is differentiated into two phases to better utilise the resources. A two-stage stochastic programming with recourse model is developed to determine the production loading plan with uncertain demand and parameters. A set of data from a toy company shows the benefits of the postponement strategy: these include lower total cost and higher utilisation of resources. The impact of unit shortage cost under different probability distribution of economic scenarios on the total cost is analyzed. Comparative analysis of solutions with and without postponement strategies is also performed.     

An application of the integrated AHP-PGP model for performance measurement of supply chain management

The performance measurement problem has gained great attention in business and operations management literature. The first objective of this study is to determine the required performance measures and to develop a model for performance evaluation, based on these selected measures using analytical hierarchy process (AHP) methodology. The second objective is to explain how an integrated AHP-PGP (pre-emptive goal programming) model can be used in performance measurement while optimising the overall performance. An integration of AHP and multi-objective PGP is used to consider both quantitative and qualitative performance measures in optimising the overall performance of the system. The integrated model is presented with a real-world application using source data provided by a survey conducted in India. Findings demonstrate that the integrated AHP-PGP model can be useful to all supply chain industries in their day-to-day performance measurement decisions.     

Supplies from developing countries: Optimal order quantities under loss risks

When raw material suppliers of a global supply chain are situated in developing countries, not only will there be long lead times but there could also be a possibility of material losses in transit. The magnitude of the losses will be uncertain and can be significant. We consider the optimization of order quantity decisions in such situations. The long lead times imply that we need to take into account the uncertainty in finished goods demands for which the raw materials are to be ordered. The order quantities have to be optimized carefully as they determine the “real options” that become available later in production plans. Using data from the plywood industry and using stochastic programming we demonstrate a method for solving such problems. The method combines simulation and optimization. An interesting observation we make is that the optimal order quantity of a material need not be monotonic in expected loss of that material. In addition, we offer explanations as to why the expected loss need not be monotonic.     

An integrated closed-loop product lifecycle management approach for reverse logistics design

Nowadays, reverse logistics is gaining importance for many companies in different industries. This importance is rooted in the fact that it generates profit and decreases the environmental impacts of products. Even though the decrease of environmental impacts is an indispensable requisite, reverse logistics design is only driven by cost indicators. The main reason behind this high cost is access to environmental information is difficult and is directly linked to data all along the lifecycle of the product. This paper presents a method by which reverse logistics design integrates environmental impacts based on the management of closed-loop product lifecycle. This method is divided into two processes: from beginning of life to end of life and from end of life to beginning of life. The first process integrates product data in order to calculate environmental impacts of the potential reverse logistics networks, whereas the second process selects the most appropriate reverse logistics network before optimising the product based on this particular network. The proposition is illustrated by a case study on a recycled aluminium automotive part.     

The project of a new of neural networks products line: An application

The aim of this paper is to propose a new approach to the issue ofpositioning and pricing a firm's new products line; it is shown here how to conceive an artificial neural system able to find the optimal solution. The formulation of the problem follows the model proposed by Dobson and Kalish, while the implementation is based on the Hopfield Neural Network, thus used here for a new class of problems. The model shows a capacity to converge to the optimal solution; besides its effectiveness, this technique appears to also be efficient if applied to such a production problem.     

Staffing a Multiskilled Workforce with Varying Levels of Productivity: An Analysis of Cross-training Policies*

Service operations that utilize cross-trained employees face complex workforce staffing decisions that have important implications for both cost and productivity. These decisions are further complicated when cross-trained employees have different productivity levels in multiple work activity categories. A method for policy analysis in such environments can be beneficial in determining low-cost staffing plans with appropriate cross-training configurations. In this paper, we present an integer linear programming model for evaluating cross-training configurations at the policy level. The objective of the model is to minimize workforce staffing costs subject to the satisfaction of minimum labor requirements across a planning horizon of a single work shift. The model was used to evaluate eight cross-training structures (consisting of 36 unique cross-training configurations) across 512 labor requirement patterns. These structures, as well as the labor requirement patterns, were established based on data collected from maintenance operations at a large paper mill in the United States. The results indicate that asymmetric cross-training structures that permit chaining of employee skill classes across work activity categories are particularly useful.     

An integrated approach for water resources decision making under interactive and compound uncertainties

In recent years, the issue of water allocation among competing users has been of great concern for many countries due to increasing water demand from population growth and economic development. In water management systems, the inherent uncertainties and their potential interactions pose a significant challenge for water managers to identify optimal water-allocation schemes in a complex and uncertain environment. This paper thus proposes a methodology that incorporates optimization techniques and statistical experimental designs within a general framework to address the issues of uncertainty and risk as well as their correlations in a systematic manner. A water resources management problem is used to demonstrate the applicability of the proposed methodology. The results indicate that interval solutions can be generated for the objective function and decision variables, and a number of decision alternatives can be obtained under different policy scenarios. The solutions with different risk levels of constraint violation can help quantify the relationship between the economic objective and the system risk, which is meaningful for supporting risk management. The experimental data obtained from the Taguchi's orthogonal array design are useful for identifying the significant factors affecting the means of total net benefits. Then the findings from the mixed-level factorial experiment can help reveal the latent interactions between those significant factors at different levels and their effects on the modeling response.     

Planning and Scheduling in Supply Chains: An Overview of Issues in Practice

This paper gives an overview of the theory and practice of planning and scheduling in supply chains. It first gives an overview of the various planning and scheduling models that have been studied in the literature, including lot sizing models and machine scheduling models. It subsequently categorizes the various industrial sectors in which planning and scheduling in the supply chains are important; these industries include continuous manufacturing as well as discrete manufacturing. We then describe how planning and scheduling models can be used in the design and the development of decision support systems for planning and scheduling in supply chains and discuss in detail the implementation of such a system at the Carlsberg A/S beerbrewer in Denmark. We conclude with a discussion on the current trends in the design and the implementation of planning and scheduling systems in practice.     

An environmental life cycle optimization model for the European pulp and paper industry

Will paper recycling reduce the environmental impact of the European pulp and paper sector? If so, is maximal paper recycling the best policy to optimize the life cycle of the pulp and paper sector? We explore these questions using an approach that combines materials accounting methods and optimization techniques. Environmental impact data are inputs for a linear programming network flow model to find optimal configurations for the sector. These configurations consist of a mix of different pulping technologies, a geographical distribution of pulp and paper production, and a level of recycling consistent with the lowest environmental impacts. We use the model to analyse scenarios with different recycling strategies. Recycling offers a reduction in environmental impact in regions with a high population and a large production of paper and board products. Regions with a large production of graphic products should focus on cleaner virgin pulp production with energy recovery. We conclude that relocation of paper production also offers a reduction in environmental impact. However, the severe effects on the economy make this policy less attractive than a combination of recycling, cleaner pulp production and energy recovery.     

Production planning and control for remanufacturing: exploring characteristics and difficulties with case studies

Production planning and control for remanufacturing is a major managerial challenge in the operations management. Researches demonstrate the need for decision-making methods in this context, which has generated theoretical and quantitative studies. However, this area still lacks empirical studies dealing with the practical, day-to-day difficulties of remanufacturers. The purpose of this paper is to link the literature and practice in a systematic in such a way that it is possible to show the similarities and differences between theoretically listed needs and real cases, thereby extending the results of previous research. For this purpose, four case studies are considered. The cases involve original equipment manufacturers (OEM) of automotive parts that have remanufacturing operations. The results indicate that these companies have difficulties that have not been addressed to date in the literature related to the uncertainties inherent in remanufacturing. In addition, we find that these companies use simplified decision-making approaches.     

Computer-aided formulation and optimal control of an integrated production system for competitive products

An integrated production, inventory and advertising system has been formulated based on control engineering principles. In this system, the customer's demand is satisfied from stock, which in turn is replenished from production facilities. But sales reflect the advertising effort, present as well as past. The past effort has been considered as a delay with an assumed delay period. The problem is formulated as a state and observation model. Out of this an augmented model of state and parameters is formed. The parameters describing the model are estimated from MAP discrete filter algorithm. It is shown that sales of product 1 or product 2 at (k + l)th period is effected by sales and advertising of product 1 or product 2 at the kth period, and also by sales and advertising of product 2 or product 1 at (k-θ)th period, where 6 is the delay.     

Evaluation of multi-objective optimization approaches for solving green supply chain design problems

This paper evaluates the applicability of different multi-objective optimization methods for environmentally conscious supply chain design. We analyze a case study with three objectives: costs, CO₂ and fine dust (also known as PM – Particulate Matters) emissions. We approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods with pre-defined or adaptively selected parameters, two popular evolutionary algorithms, SPEA2 and NSGA-II, with different selection strategies, and their interactive counterparts that incorporate Decision Maker׳s (DM׳s) indirect preferences into the search process. Within this case study, the CO₂ emissions could be lowered significantly by accepting a marginal increase of costs over their global minimum. NSGA-II and SPEA2 enabled faster estimation of the Pareto front, but produced significantly worse solutions than the exact optimization methods. The interactive methods outperformed their a posteriori counterparts, and could discover solutions corresponding better to the DM preferences. In addition, by adjusting appropriately the elicitation interval and starting generation of the elicitation, the number of pairwise comparisons needed by the interactive evolutionary methods to construct a satisfactory solution could be decreased.     

ICT-based solution approach for collaborative delivery of customised products

Growing interest on business collaboration motivates today’s industries, especially small and medium enterprises (SMEs) to establish and manage dynamic and non-hierarchical business networks to respond to market opportunities with added business benefits. This business environment requires concurrent work and real-time information sharing between key business partners in order to design and develop customised products. The use of traditional communication media such as e-mail, phone and fax is not satisfactory to get real-time information and is time-consuming and most often ineffective. In such environments, an Information and Communication Technology (ICT)/Web-based technology supports real-time information sharing among networked SMEs for the collaborative design and manufacturing of customised products. This study proposes an innovative ICT platform supporting SMEs collaboration, through Web and the Internet of Things technologies, which follows the Net-Challenge conceptual approach and methodological guidelines for SMEs to form and operate virtual organisations for the collaborative development and delivery of customised products. The ICT Platform was assessed in three different industry domains, namely the textile and apparel, the footwear and the machine tools, respectively. This ICT solution promotes collaboration, with substantial advantages for SMEs including the reduction of costs and delivery time and improvement of the innovation potential.     

Inventory control for the supply chain: An adaptive control approach based on the identification of the lead-time

In this paper, an Internal Model Control (IMC) scheme is incorporated in production inventory control systems in a complete supply chain. This control scheme presents a good target inventory tracking under the perfect knowledge of the system. Furthermore, the inventory tracking and load disturbance rejection control problems can be tackled separately. However, the closed-loop performance of the IMC scheme may be degraded due to a mismatch between the modelled and actual delay or to the fact that delays may be time-varying. Thus, the IMC control scheme is enhanced in this work with a novel method for the online identification of lead times based on a multimodel scheme. In this way, all benefits of the IMC scheme can be exploited. A detailed discussion of the proposed production inventory system is provided including a stability and performance analysis as well as the identification capabilities of the algorithm. Several simulation examples illustrate the efficiency of the approach.