Figure 2 - uploaded by Wakhid Ahmad Jauhari
Content may be subject to copyright.
Source publication
Purpose: The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification.
Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detail...
Context in source publication
Similar publications
![Piston-cylinder bore assemblage [8]](profile/Krishnaraj-Ramaswamy/publication/362566816/figure/fig1/AS:11431281200067032@1697768299040/Piston-cylinder-bore-assemblage-8_Q320.jpg)
In order to have a competitive edge, manufacturing companies have to develop superior quality products at minimum cost. Tolerance design is the most critical part of concurrent engineering in which optimal values of tolerances have to be determined for all components of an assembly, with due consideration towards the cost as well as quality. In thi...
Citations
... Janjić Goran et al. [25] considered the impact of parts outsourcing policies and proposed an OEM-led quality management model for incoming parts in the automobile industry, though the coordination model for the supplier's specific production process had not yet been provided. Rosyidi C N et al. [26] developed a parallel design model of supplier selection and component allocation, considering multiple constraints such as the production capacity of suppliers, assembly quality, techniques, and technical capability, and with the purpose of minimizing procurement cost and fuzzy quality loss. By adopting the asymmetric tolerances Taguchi capability index as a data-driven supplier selection tool, Chin-Hsin Wang [27] established a comprehensive supplier selection model based on process quality. ...
Automobile manufacturers often outsource key components and parts to suppliers, hence ensuring that process quality has been a hot topic in current research. The quality control demands at different stages of the manufacturing supply chain cycle have been ignored in traditional process quality control methods. To solve this issue, this paper takes the three-cylinder engine balance shaft system as the research object, and builds a process quality control model for the three-cylinder engine balance shaft system oriented to the manufacturing supply chain. The metagraph theory is introduced, and parts suppliers in the manufacturing supply chain, product process quality attributes, supply chain revenue function, and other key elements are defined. By constructing the revenue function of the three-cylinder engine balance shaft system process quality control model, the feasibility of the proposed method is verified by taking the process quality control of one certain three-cylinder engine balance shaft system as a verification example. The results show that, with other conditions unchanged, the application of this method can increase the overall profit of the manufacturing supply chain by 100% at the stage of preparation before product machining, and more than 8% at the stage of product performance evaluation. The proposed method of process quality control based on the metagraph theory provides a theoretical basis for building an information sharing platform of product process quality, and effectively reduces the machining cost for product improvement and upgrading in the manufacturing supply chain.
... The fuzzy concept was first introduced by Zadeh in 1965, to alleviate uncertainties and fuzziness problems. The technique relies on human subjectivity in decision-making due to linguistic variables that allow precise modeling of imprecise entrances [7,8] and has been applied to many engineering problems [9,10]. This concept offers a number of advantages for users, such as reducing the costs of production, transport, storage, and recovery as well as improving the costs of the companies using it [11,12]. ...
This paper presents a fuzzy quality certification of wheat. This analysis is based on the fuzzy analysis model of wheat. We developed a Matlab application with the help of which we modeled the perceptions in relation to the main quality physical and chemical characteristics of wheat obtaining a quality index of wheat lots. The algorithm presented in this article allows for obtaining and using the global quality index, generating applicability not only to the commercial sphere as a quality reference and price setting, but also a measure of appreciation of processing opportunities. Indices of fuzzy quality associated with wheat lots using a fuzzy model offer the opportunity to develop local markets through quality certification.
... The problem of supplier selection and order allocation was solved in the paper [3] in a closedloop supply chain using Monte Carlo simulation and goal programming. Rosyidi et al. [20] proposed a model for concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Gheidar-Kheljani et al. [21] solved the problem of supply chain optimization policy for supplier selection by applying a mathematical programming approach. ...
... In Eq. (20), λ is chosen by decision-makers and is usually λ = 0.5. ...
Procurement logistics is one of the most important segments of the supply chain and one of the key factors of a company's competitiveness. For that reason, many companies strive for constant optimization of this segment of the supply chain, both in terms of costs and in terms of time, reliability, etc. The aim of this paper is to develop a new approach based on DEA-FUCOM-CoCoSo methods that aim to select efficient suppliers. The developed model was tested on the data of one trading company. The DEA method was used in order to select only efficient ones from 29 observed in this paper. The FUCOM method was used to determine the weights of the 9 observed criteria used in the CoCoSo method for evaluation of 6 efficient suppliers. The results of the application of this method determined the final rank of suppliers, after which only the first 3 suppliers were considered. At the very end, a model for solving the problem of order allocation is defined in order to determine from which supplier it is necessary to order goods and in what quantity. By applying the defined model, the quantities that need to be ordered from certain suppliers in order to meet the demand on the market are obtained. Based on the results, the developed approach showed the possibility of large application not only on the observed example but also on a larger problem.
... The model only allowed one supplier selected for each component assuming that the selected supplier has enough capacity to supply the needed components. Based on that model, Rosyidi et al. (2017) developed an optimization model similar to Feng et al. (2001) by allowing more than one supplier selected and including the fuzzy quality loss to accommodate uncertainty in the quality level. ...
A company has to produce a product that gives better value than its competitors. It means the company has to produce a better quality product with lower manufacturing cost. Outsourcing has become a common practice in manufacturing where a company outsources some of their needed components to the suppliers. Supplier selection is not an easy task since it will determine the manufacturing cost and quality of the product. In this research, we develop a two-stage optimization model to help decision maker in determining the optimal suppliers which will give least manufacturing cost and how to improve the quality of the components. In the first stage, a process/supplier selection model was developed to determine the optimal tolerance and component allocation to minimize manufacturing cost and quality loss. In the second stage, investment allocation model was developed to improve the quality of the components. The objective function of the second model is to maximize the return on investment (ROI). The implementation and analysis of the proposed model were demonstrated using a simple assembly product which consists of three components and solved using Oracle Crystal Ball software.
Aiming at the problem of product processing quality management in automobile manufacturing supply chain, the concepts of automobile manufacturing supply chain and medium auto parts enterprise are put forward, the theory of product life cycle and relationship life cycle is introduced, and the automobile manufacturing supply chain is divided into product processing preparation stage, product sample performance evaluation stage and product production and operation stage. The cooperation model of the medium enterprise in the automotive manufacturing supply chain is constructed, the management characteristics and key influencing factors of the medium auto parts enterprises in the three stages of the automotive manufacturing supply chain are analyzed, and from the perspective of the supply chain, the product processing quality management demand model of the medium enterprise is established. Taking a new product manufacturing of an auto parts enterprise in China as an example, the practicability and rationality of the proposed concept and model are verified.
Dimensional tolerance allocation is a very important and difficult task that traditionally seeks to balance cost/productivity and quality. Common tolerance allocation models have two shortcomings: i) they are overly reliant on models focused on minimizing cost and tend to ignore waste, and ii) they fail to connect to the root cause of many quality issues: process variation. This paper proposes a tolerance allocation model that addresses these shortcomings. The proposed model considers both product design (tolerance selection) and operation planning (or production rate selection). Relations among production rate, production cost, processing precision, and waste are considered. A gradient-based optimization method is proposed to minimize the cost and waste. A clutch assembly case study is analyzed to evaluate the method. Monte Carlo simulations are employed to validate the accuracy of the proposed cost model. The proposed method is compared with a heuristic method from the literature. The proposed method produced more satisfactory products at a lower cost while producing less waste. For the case study, it is found that when the precision of a process is high, it is not necessary from an economic standpoint to inspect the quality of individual components. For poor precision processes, inspecting the quality of individual components is the preferred approach from a cost/throughput standpoint.
It is widely acknowledged that the allocation of part tolerances is a highly responsible task due to the complex repercussions on both product quality and cost. As a consequence, since its beginnings in the 1960s, least-cost tolerance allocation using optimization techniques, i.e. tolerance-cost optimization, was continuously in focus of numerous research activities. Nowadays, increasing cost and quality pressure, availability of real manufacturing data driven by Industry 4.0 technologies, and rising computational power result in a continuously growing interest in tolerance-cost optimization in both research and industry. However, inconsistent terminology and the lack of a classification of the various relevant aspects is an obstacle for the application of tolerance-cost optimization approaches. There is no literature comprehensively and clearly summarizing the current state of the art and illustrating the relevant key aspects. Motivated to overcome this drawback, this article provides a comprehensive as well as detailed overview of the broad research field in tolerance-cost optimization for both beginners and experts. To facilitate the first steps for readers who are less familiar with the topic, the paper initially outlines the fundamentals of tolerance-cost optimization including its basic idea, elementary terminology and mathematical formulation. These fundamentals serve as a basis for a subsequent detailed discussion of the key elements with focus on the different characteristics concerning the optimization problem, tolerance-cost model, technical system model and the tolerance analysis model. These aspects are gathered and summarized in a structured mind map, which equips the reader with a comprehensive graphical overview of all the various facets and aspects of tolerance-cost optimization. Beside this, the paper gives a retrospect of the past fifty years of research in tolerance cost-optimization, considering 290 relevant publications. Based thereon, current issues and future research needs in tolerance-cost optimization were identified.
Purpose
The purpose of this paper is to evaluate the agility performance level of manufacturing supply chains using Taguchi Loss Functions (TLFs) and Design of Experiment (DoE).
Design/methodology/approach
The proposed methodology is used for capturing the various agility losses using appropriate TLFs and the aggregated agility loss is calculated at different situations using DoE. The aggregated agility loss is analyzed for comparing manufacturing supply chain agility performance.
Findings
The proposed methodology was applied to three Indian auto component supply chains i.e. X, Y and Z. Twenty seven experiments were carried out using DoE and obtained results show that agility performance level is the highest for X followed by Z, whereas agility performance level is the least for Y.
Research limitations/implications
The proposed methodology is generic in nature and can be applied to a specific environment for comparing performance of different supply chains. The user has to identify the relevant agility enablers and capture the appropriate TLFs for the specific environment in which agility performance level has to be calculated and compared.
Practical implications
The proposed methodology provides an effective approach for evaluating agility performance. It can be used by the supply chain manger to assess the supply chain agility performance level of own company with its competitors. These comparisons will help the manufacturing company to find the areas where it should focus.
Originality/value
Many studies and researches related to implementation and evaluation of agile manufacturing are reported in the literature but very few studies are available for evaluating the supply chain agility performance. This study will definitely provide a guideline for measuring and comparing manufacturing supply chain agility performance in general and Indian automotive supply chain in specific.
