Green supply chain network design under uncertainty conditions with the mathematical model and solving it with a NSGA II algorithm

Purpose: In this paper a mathematical model for the green supply chain network problem is designed. In this research, we seek to optimize two inconsistent and conflicting goals of the problem which are as follows: 1.Minimization of costs 2.Minimization of environmental impacts, using of the economic indicator 99 method. Methodology: In this paper, two methods of Epsilon constraint and NSGA II algorithm are used to solve the two-objective model with the objective functions of minimizing network costs and minimizing emissions. Findings: The results show that the introduced NSGA II algorithm has a high efficiency in forming efficient solutions in a short time. Originality/Value: In this paper, a two-objective model for green supply chain network is modeled and solved with the aim of reducing network costs and reducing greenhouse gas emissions

Overall Equipment Effectiveness: Systematic Literature Review and Overview of Different Approaches

Overall equipment effectiveness (OEE) is a key performance indicator used to measure equipment productivity. The purpose of this study is to review and analyze the evolution of OEE, present modifications made over the original model and identify future development areas. This paper presents a systematic literature review; a structured and transparent study is performed by establishing procedures and criteria that must be followed for selecting relevant evidences and addressing research questions effectively. In a general search, 862 articles were obtained; after eliminating duplicates and applying certain inclusion and exclusion criteria, 186 articles were used for this review. This research presents three principal results: (1) The academic interest in this topic has increased over the last five years and the keywords have evolved from being related to maintenance and production, to being related to lean manufacturing and optimization; (2) A list of authors who have developed models based on OEE has been created; and (3) OEE is an emerging topic in areas such as logistics and services. To the best of our knowledge, no comparable review has been published recently. This research serves as a basis for future relevant studies

The human performance impact on oee in the adoption of new production technologies

Featured Application This research work proposes a framework for the evaluation of the initial adoption phase of new production technologies and its application to the introduction of a semi-automatic packaging machine in a relevant logistics company. The case study allowed the assessment of the machine ramp-up phase and provided valuable insights for reducing the length of this period by achieving a stable target production output. Moreover, it shows how the framework can be adopted, applied and interpreted for obtaining useful insights. Manufacturing systems in digital and interconnected industrial settings where human worker activity is required represents further potential applications of this paper. The initial adoption phase of new production technologies is the period between the first production run or technology reconfiguration and the achievement of a stable target output. This time frame is generally characterized by productivity unsteadiness, quality performance variability, and unexpected machine failures together with increasing production volumes due to the process setup and instability, which inevitably affects production output. In this context, human performance represents an additional source of variability and process instability that is dependent on the workers' productivity, learning curve and related training activities. Hence, to effectively assess the ramp-up phase of new production technologies, an appropriate evaluation of human performance is required. This paper proposes a comprehensive framework and criteria to perform a consistent assessment of the initial adoption phase of new production technologies by introducing two OEE measurement methodologies that distinguish between human performance, process configuration and technical features of the production technology. The proposed framework is then applied to and validated by a case study concerning the introduction of a semi-automatic packaging machine in a primary multinational company in the logistics industry. This case study shows the difference between the two OEE measures, along with the values interpretation and useful insights for achieving a stable production output

Design Supply Chain Based on Cost of Quality with Consideration of Quality Level

In the contemporary global market, organizations are striving to survive and compete not only by satisfying customer’s needs but also by fulfilling it with the least costs. Quality management experts determined that quality costs account for a substantial part of total production costs. Therefore, finding a way to improve the Quality Level (QL) while minimizing the Cost of Quality (COQ) is a crucial task. In the manufacturing industry, there are a variety of costs that are directly associated with the production; these costs can be considered as visible costs. However, another type of costs may indirectly arise during and after manufacturing processes or even after the product reaches the customer. These types of costs are considered as invisible (hidden) costs and in most cases are difficult to track. Measuring the effect of hidden costs such as the costs of unsatisfying a customer is not straightforward. Even though the hidden costs may have serious consequences for any organization if they are not considered in early stages, they are rarely incorporated in the COQ calculations. Furthermore, the COQ models found in the literature rarely go beyond the costs incurred within an individual firm and seldom attempt to estimate cost elements related to the customers or suppliers. This, however, does not reflect the reality, since not all the quality costs are generated internally. Suppliers, subcontractors, agents, dealers and customers each contribute (sometimes significantly) to an organization's indirect quality costs. It is therefore proposed to combine the internal measures of COQ with costs related to both upstream and downstream supply chain (SC) partners. In this thesis, pursuing the aforementioned motivations, we focus on designing SCs in framework of various COQs and QLs. The previous literature lacks a work that integrates the opportunity cost (OC), COQ and QL into SC and Supply Chain Network Design (SCND). The main objectives of this thesis are to consider OC in the COQ analysis, to incorporate it into the Prevention, Appraisal, and Failure (PAF) model, and to analyze it together with various QLs in a manufacturer SC. The purpose is to find an optimum QL that matches the minimum spending on the COQ and. This work proposes a reliable COQ model, which can be used to measure COQ in the whole SC. We carried out a case study in a manufacturing SC to collect the PAF data and the related data to OC i.e., customer satisfaction. The involved organization is an automobile manufacturing SC. A system dynamics model is used to simulate the COQ, while including OC and analyzing its effects at different QLs. In addition, PAF, OC, and QL are mathematically modeled in an uncapacitated SC. Different proposed scenarios were developed to allocate the PAF, OC, and QL in the SC. The model determines the best scenario of allocating the COQ at each facility while minimizing the COQ and OC, and thereby optimizing the QL. Based on the COQ, the mathematical model also reveals the difference between the centralized and decentralized SC. Moreover, we address the effects of spending limitations of PA costs on F, OC, and QL at each facility and in the SC as a whole. Afterwards, the thesis develops a mathematical model which is involved in designing of a capacitated SCND based on PAF, OC, and QL. The developed model is intended to highlight the importance of OC by show the difference between OC-included and OC-excluded SCND model. The SCND model is also used to determine the best improvement in the QL, i.e. the optimal value of investing in the COQ at each echelon. Finally, a hybrid decision support system (DSS) model which combines the mathematical model and the simulation model for COQ, OC, and QL is developed. The model implements the optimum results of the mathematical model in the simulation model. This aim is to increase spending on PA costs beyond the optimal results of the mathematical model. The model is intended to decrease the OC (increase the number of new customeers). The results show how the combined methodologies can provide better decision support for upper management. This research shows that COQ can be used as a meaningful measure of improvement not only in an organization but in the whole SC. The methods developed in this thesis will provide a powerful tool to management for assessing quality economics, facilitating quality programs and optimizing benefits of quality across SC

Food supply chain management and contracting: improving conditions for small-scale paprika farmers in central Malawi

Global population growth and increasing incomes across the world are resulting in consumers’ rising demand for quality and diverse foods. Trade liberalisation and modernisation of production, processing and distribution systems enable agro-food companies to quickly access raw materials from farmers. Thus, efficient supply chains have a key role to play in the global marketing of foods. They also significantly contribute to satisfying consumers’ needs and responding to emerging food trends. The organisation of the product flow among farmers, buyers, processors and customers through contracts represents an increasingly important marketing channel in modern food supply chains due to its potential to decrease costs and increase profits for the participants in the chain. However, vulnerable small-scale farmers in developing countries such as Malawi are often excluded from the benefits of the transformed food industry. Contract farming is recognised as one of the tools linking farmers with modern agro-food supply chains, which enables Malawian small-scale farmers to improve their livelihoods. This study explored, examined and addressed the key challenges in contract farming arrangements in the paprika supply chain in Central Malawi. A mixed methods approach was used to collect qualitative and quantitative data. A total of 428 household questionnaires were administered to contracted small-scale paprika farmers in two Malawian districts. These were supplemented with ten focus group interviews with small-scale farmers, 21 semistructured stakeholder interviews, ten expert semi-structured interviews, field observations and two focus group discussions with stakeholders. The study found that the quality of communication among the key participants in the paprika supply chain was low. Furthermore, the enabling environment provided limited access to input and services for small-scale farmers. The paprika contract secured quality seeds and extension services to contracted small-scale farmers. Nevertheless, the provision of fertilisers, pesticides, chemicals, storage and transportation services were not part of the Malawian contract. Poor contract design and side-selling practices posed a threat to the chain’s efficiency and sustainability. Small-scale farmers gained benefits from the contracted production but contracting itself was not a sufficient strategy to sustain their livelihoods throughout the year. More dedicated involvement of farmers’ organisations and NGOs in empowering small-scale farmers, and the Government’s presence through the national Contract Farming Strategy could contribute to better efficiency and sustainability of the chain. The study’s main contributions include: adding new evidence on contract farming performance in developing countries; highlighting the importance of contract design and the issue of side-selling for improved contracting conditions, and demonstrating how dissemination of the study’s findings can be incorporated into study design to increase the validity, rigour and impact of the research