Two stages optimization model on make or buy analysis and quality improvement considering learning and forgetting curve

Purpose: The aim of this research is to develop a two stages optimization model on make or buy analysis and quality improvement considering learning and forgetting curve. The first stage model is developed to determine the optimal selection of process/suppliers and the component allocation to those corresponding process/suppliers. The second stage model deals with quality improvement efforts to determine the optimal investment to maximize Return on Investment (ROI) by taking into consideration the learning and forgetting curve. Design/methodology/approach: The research used system modeling approach by mathematically modeling the system consists of a manufacturer with multi suppliers where the manufacturer tries to determine the best combination of their own processes and suppliers to minimize certain costs and provides funding for quality improvement efforts for their own processes and suppliers sides. Findings: This research provides better decisions in make or buy analysis and to improve the components by quality investment considering learning and forgetting curve. Research limitations/implications: This research has limitations concerning investment fund that assumed to be provided by the manufacturer which in the real system the fund may be provided by the suppliers. In this model we also does not differentiate two types of learning, namely autonomous and induced learning. Practical implications: This model can be used by a manufacturer to gain deeper insight in making decisions concerning process/suppliers selection along with component allocation and how to improve the component by investment allocation to maximize ROI. Originality/value: This paper combines two models, which in previous research the models are discussed separately. The inclusions of learning and forgetting also gives a new perspective in quality investment decision.Peer Reviewe

The impact of quality management system of contactor quality performance at a local power station in South Africa

Abstract: The purpose of this study is to evaluate the impact of Company X QMS on the contractors’ quality performance. The study will also determine how Company X’s QMS can be utilized to improve the quality performance of its contractors. The survey conducted evidently shows that one element was utilized to enforce contractors to comply with the quality requirements, and that is the implementation of Quality Control Plan (QCP) that is approved by Company X’s Quality Department before execution of any project. Findings indicate that Company X needs to integrate quality requirements in the procurement process to ensure that contractors understand the quality expectations and requirements in its contractor management process

Two Stage Procurement Processes With Competitive Suppliers and Uncertain Supplier Quality

This paper considers a sourcing problem faced by a manufacturer who outsources the manufacturing of a product to one of several competing suppliers, whose cost and quality capabilities are unknown. We consider a two-stage sourcing process in which the first stage is the qualification stage, while the second stage is the supplier selection stage. In the first stage, the manufacturer exerts effort to learn about the quality level of each of the suppliers and then must determine the set of qualified suppliers, subject to some tolerance for error. In the second stage, the manufacturer runs a price-only procurement auction, in which the qualified suppliers compete for the manufacturer’s business.We model this two-stage sourcing process with the goal of obtaining insights into manufacturer’s optimal decisions. We seek to determine the optimal qualification standard, the optimal amount of effort to be exerted in the qualification process and the appropriate tolerance for error in the qualification process, and to understand the interactions between these decision variables. We are particularly interested in understanding how the manufacturer can design the process to 1) ensure the firm only sources from qualified suppliers and 2) encourage competition among the suppliers during supplier selection

Reprint of "Decision support models for supplier development: Systematic literature review and research agenda"

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

Reprint of "Decision support models for supplier development: Systematic literature review and research agenda"

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

Methodology for the collaboration in supply chains with a focus on continuous improvement

A collaborative relationship between companies in a supply chain makes it possible to improve both the performance and the results of the companies and of the supply chain. Several studies have analyzed supply chains, but few studies have proposed the application of tools for continuous improvement in a collaborative manner within the supply chain. The objective of this work is to present a methodology for the collaboration in a supply chain with a focus on continuous improvement. Three case studies were conducted with Brazilian multinational focal companies that manufacture technology-based products. It was seen that relationships, trust, the exchange of information, and the sharing of gains and risks sustains collaborative practices focused on continuous improvement. The proposed methodology considers the need for supplier development, for the monitoring of the supplies, and for the development of a partnership for problem solving through the application of tools for continuous improvement.Una relación de colaboración entre una cadena de suministro permite a las empresas mejorar el rendimiento y los resultados de las empresas y de la cadena de suministro. Hay varios estudios que se ocupan de las cadenas de suministro, pero son pocos los estudios que apuntan a la aplicación de herramientas colaborativas para lograr una mejora continua en la cadena de suministro. El objetivo de este trabajo es presentar una metodología para la colaboración en la cadena de suministro, enfocado en una mejora continua. Se realizaron tres estudios de caso en empresas multinacionales brasileñas que fabrican productos de base tecnológica. Se observó que las relaciones, la confianza, el intercambio de información, y la participación conjunta en riesgos y beneficios sustentan las prácticas colaborativas enfocadas hacia una mejora continua. La metodología propuesta considera la necesidad del desarrollo de proveedores, la supervisión de los suministros, y la colaboración en la solución de problemas a través de la aplicación de herramientas de mejora continua

Carbon-optimal and carbon-neutral supply chains

Carbon footprinting is a tool for firms to determine the total greenhouse gas (GHG) emissions associated with their supply chain or with a unit of final product or service. Carbon footprinting efforts typically aim to identify where best to invest in emission reduction efforts, and/or to determine the proportion of total emissions that an individual firm is accountable for, whether financially and/or operationally. A major and under-recognized challenge in determining the appropriate allocation stems from the high degree to which GHG emissions (or emissions reductions) are the result of joint efforts by multiple firms. In this paper we introduce a simple but effective model of joint production of GHG emissions in general supply chains, decomposing the total footprint into processes, each of which can be influenced by any combination of firms. A supply chain in which all firms exert their first-best emissions reduction effort levels is "carbon optimal", while a supply chain which offsets all emissions is "carbon neutral". With this structure, we examine conditions under which the supply chain can be carbon-neutral and/or carbon-optimal. We find that, in order to induce the carbon-optimal effort levels, the emissions need to be over-allocated. This means that the focus in the life-cycle assessment (LCA) and carbon footprinting literature on avoiding double-counting is, in the context of setting incentives, misguided. We also compare the situation where a single firm offsets all supply chain emissions with that where one powerful firm can enforce an emissions reduction target across all firms in the supply chain, and find that neither scenario is always preferred over the other. Our work aims to lay the foundation for a framework to integrate the economics- and LCA-based perspectives on supply chain carbon footprinting

Policies for improving quality in supply chain

This paper is aimed to analyse the problem associated with quality in a two-stage supply chain with one supplier and one manufacturer. Most cases in real life is not this simple, although for the propose of keeping easy for calculations, even if there’re several suppliers we can simplify it to only one supplier that provides different quality level products. A mathematic model is built to simulate the problem and we will analyse the problem into two real cases, which will be detailed in the paper. Finally, we aimed to get some conclusions from these cases

Quality Control Along Supply Chain

Product quality is the core competitiveness of a brand, prompting brand-owner continuously to pursue. Learning curve is the tool to improve product quality by variance reduction. At the same time, knowledge depreciation with its negative effects attracts attention. Thus, a comprehensive learning curve is introduced in this dissertation. This research focus to explore the quality improvement along the supply chain. There are three contributions in this dissertation: 1) it provides the supply chain’s optimal distribution of quality improvement to manufacture and its suppliers; 2) it shows the benefit from coordinated quality improvement among the supply chain; 3) it illustrates the benefit from increased demand and decreased cost from quality improvement. Three models are presented consecutively in this dissertation. The first model assists the supply chain to coordinate all suppliers for quality investment. Based on the traditional learning curve, the comprehensive learning model is introduced in order to better understand the knowledge accumulation effect. Autonomous learning, induced learning and their respective knowledge depreciation effects are considered in this model. The product quality is measured from several aspects, and each aspect linearly depends on the component quality. Therefore, suppliers’ quality improvement contribute to the end product quality. The second model further considers each outsourced components have interaction effects. To better understand knowledge forgetting effect, it adopt Weibull distribution to simulate producing disruption. What’s more, it considers the optimal quality investment for the whole producing system and a suboptimal quality investment when there is no coordination in the system (Dyadic Supply Chain). Without coordination, every supplier is trying to save her own quality cost, but the total quality cost is higher than the coordinated system. Thus, incentives are necessary to these suppliers to cooperate in quality improvement. In addition, the second model provides existence proof of the optimal solution. Since the previous models using variance reduction to save cost, it increases demand as well. The third model starts to consider demand increasing and quality saving simultaneously. Similar to model 2, the third model compares the optimal quality efforts under the coordinated system and the sub-optimal quality efforts under un-coordinated system. Generally, the coordinated system is more efficient. With coordination, 1) marginality is eliminated; 2) cost is lower; 3) demand is higher from higher quality. Since supplier invest more with cooperation, incentives is required to all suppliers