Thirty criteria based leanness assessment using fuzzy logic approach

Nowadays manufacturing organizations are moving towards lean practices to keep pace with the competition. Lean practices mainly focuses on eliminating seven deadly wastes, thereby reducing the cost. Leanness is the measure of lean manufacturing practices. This paper presents the 30 criteria based leanness assessment methodology using fuzzy logic. Fuzzy logic has been used to overcome the disadvantages with scoring method such as impreciseness and vagueness. During this research, a conceptual model for leanness assessment has been designed. Then the fuzzy leanness index which indicates the leanness level of the organization and fuzzy performance importance index which helps in identifying the obstacles for leanness has been computed. The results indicate that the model is capable of effectively assessing leanness and has practical relevance.     

Leanness evaluation using IF–THEN rules

Lean manufacturing is a manufacturing system aimed at waste elimination thereby streamlining the process. Leanness is the performance measure of lean manufacturing. The measurement of leanness necessitates fuzzy logic, due of the existence of impreciseness and vagueness. The calculation of leanness using fuzzy logic manually is a time consuming and highly repetitive job. To overcome this, fuzzy logic-based inference method has been attempted in this research study. A conceptual model consisting of three levels namely enabler, criterion, and attributes has been developed. Then the linguistic variables are assigned and the membership functions are defined. Leanness level has been computed using IF–THEN rules based interface method. This is followed by gap analysis to identify the weaker criteria. Then suitable proposals have been derived to overcome these obstacles towards leanness improvement of the organization.     

基于Agent网的知识网自重构的需求评价模型

知识化制造系统自重构中需要有评价策略对自重构后的系统进行评价。本文从知识网需求的模糊关系出发,定义了基于agent网的知识网模糊需求的自重构运算,提出了知识化制造系统的模糊需求评判的方法,并通过一个简化的例子,说明了知识网的自重构及其模糊需求评判的方法,解决了知识网自重构后的评价问题,为知识化制造系统的决策提供了依据。     

A dynamic modeling to measure lean performance within lean attributes

In today’s competitive world lean manufacturing has become an important “role model” for two groups: academics and practitioners. Many organizations around the world have attempted to implement it but the lack of a clear understanding of the main attributes to leanness, lean performance and its measurement contribute to the failure of lean practices. It therefore seems necessary to provide a way to evaluate the impact of lean attributes using an approach to determine the criteria and key factors of leanness. Although there are numerous theoretical and practical studies that address lean tools and techniques, few studies focus systematically on measuring the influence of lean attributes on leanness. To fill the current gap, this paper presents an innovative approach to measure the value of the influence of lean attributes on manufacturing systems by using fuzzy membership functions. A lean attributes score is finally calculated to give managers and decision makers a real insight into the leanness level and to further improve it by acting appropriately in the manufacturing system. The model is dynamic, flexible, feasible, and easy to follow and implement. It enables a systematic measurement of the influence of lean attributes by producing a final integrated unit score.     

基于模糊物元与熵权分析的供应商选择评价方法研究

供应商选择与评价是学术界和工业界十分关注的优化决策问题,作为复杂的多目标决策问题,其对于企业的发展有重要的影响和意义。为克服传统供应商选择过程中的主观因素对评价目标和结果的不利影响,针对模糊物元分析和熵权法在解决矛盾不相容问题以及权重客观选择上的特点,将候选方案与最优和最次方案进行比较并计算出相应的客观权重,建立了基于物元分析和熵权的供应商选择评价方法。最后以某制造企业供应商选择过程为例,证明了该模型的可行性和有效性。     

Evaluating the flexibility in a manufacturing system using fuzzy multi-attribute group decision-making with multi-granularity linguistic information

Evaluation of flexibility in a manufacturing system development in operations management is important to determine the competitiveness of manufacturing system, and is being increasing discussed in the literature on manufacturing system. This paper presents a fuzzy group decision-making model with different linguistic term sets (multi-granularity linguistic term sets) for evaluating manufacturing flexibility development, where the performance rating of manufacturing systems under flexibility metrics and the importance grade of all flexibility dimensions are assessed in linguistic terms represented by trapezoidal fuzzy numbers. The linguistic term sets chosen by decision-makers will have more or less terms. This paper proposes a procedure to assess the degree of manufacturing flexibility in a fuzzy environment by a fuzzy fusion method of linguistic information. While evaluating the degree of manufacturing flexibility, one may find the need for improving manufacturing flexibility, and determine the dimensions of manufacturing flexibility as the best direction to improvement. Example using a case of leading Taiwan firm in the bicycle industry is used to illustrate the computational process of the proposed method.     

面向绿色制造的一类模糊调度模型及其算法

绿色制造是一种综合考虑环境影响和资源效率的现代制造模式，由于其生产系统的复杂性和不确定性，使得工序的加工时间和生产成本等数据用模糊数表示更加符合生产实际。为优化调度过程中的产品质量、生产成本、资源消耗、环境污染和生产周期，建立了面向绿色制造的模糊调度模型。将多目标遗传算法与模糊优选技术相结合对该模型求解，并用案例验证了模型的实用性和算法的可行性。     

实施绿色制造的综合风险评价

随着工业的发展,工业风险问题日益严重,种类越来越繁杂。由此,在全新的绿色制造模式实施的过程中必然存在着大量不确定的因素和高的风险。在绿色制造方面,由于缺少成功的实例和相关的理论知识,对于需要大量相关样本的以概率表示风险的方法已不适应于绿色制造项目的风险决策。针对这个问题,提出了一种基于模糊多属性决策的方法:建立了三层的层次决策框架模型;给出了模糊多属性决策的方法;然后实例研究表明该决策方法是有效的,层次决策框架模型和模糊多属性决策反映了实施绿色制造项目中的风险特点,实际应用是可行的。     

A Fuzzy Multi-Criteria Decision-Making Technique for Evaluation of Scheduling Rules

When examining manufacturing systems using simulation models, different combinations of scheduling rules can be applied to the models. Each combination satisfies a very limited number of performance measures. The problem now is "how to evaluate these combinations" and "how to reflect the weighting of each performance measure in the system". Evaluation of scheduling rules is an inevitable task for any scheduler. Only a few evaluation procedures of the results obtained from computer simulation were found in the literature. In this paper, a framework for the evaluation of combinations of scheduling rules has been developed using fuzzy multi-criteria decision-making techniques, which are called MAW, Max–Min, and Max–Max. A simulation model is used to illustrate the proposed techniques. The results are compared with a simple approach for multi-criteria decision-making method, which is called SAW. Results show that MAW is the best technique for obtaining a high score in the analysis.     

概念设计方案评价的模糊多准则决策模型

提出了一种概念设计方案评估的模糊多准则决策方法,以降低决策者主观偏好以及评估过程中模糊和不确定因素对决策的影响.基于对影响产品竞争力因素的分析,建立了概念设计方案评价的层次结构.建立了概念设计方案评估的模糊多准则决策数学模型,并以三角模糊数代替常规层次分析法中的标度,提出了一种模糊层次分析方法来确定评价体系中各级评价准则的权重,充分考虑多领域专家的意见和产品开发过程的风险性.最后,以应用实例对提出模型的有效性和可行性进行了验证.     

A comprehensive decision-making structure for acceptance/rejection of incoming orders in make-to-order environments

Several incoming orders must be considered and evaluated in terms of many different conflicting criteria for acceptance/rejection in a make-to-order manufacturing system, leading to a large set of subjective or ambiguous data. Hence, an effective evaluation approach is essential to improve decision quality. In this paper, a comprehensive decision-making structure composed of two phases is proposed to manage incoming orders. At the first phase, the new arriving orders are evaluated based on their due dates and material arrival times. At the second phase, a novel hybrid methodology consisting of analytic hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) is presented for acceptance or rejection of the first phase accepted orders based on the manufacturing system capacity. In this study the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore we apply fuzzy AHP methodology to determine the relative weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.     

A technique for advanced manufacturing systems capability evaluation and comparison (ACEC)

This paper proposes a generic technique for the evaluation and comparison of the capability of manufacturing systems as a decision-making aid. It provides a methodical approach for extracting key capability factors (CF) and their degree of fulfilment by the institutes. The capability factors and their priorities are determined by experts in the related industry. By adopting this approach, a “capability index” for each institute will be derived. This will be the basis for capability comparison. The proposed method applies fuzzy relations and analytic hierarchy process (AHP) techniques to calculate capability indices. The case study discussed in this paper is the result of a project commissioned by a prominent UK based company (UBC) to consolidate its EU operations. The results illustrate the effectiveness and flexibility of the proposed methodology for a wide range of applications.     

A New Approach to Fuzzy Part-Family Formation in Cellular Manufacturing Systems

Group technology (GT) is one of the major issues in successful implementation of cellular manufacturing systems. The success of GT implementation depends only on an effective formation of part-families. The effective formation of part-families depends mainly on an effective formation of a similarity coefficient measure. Many similarity coefficients have been produced over the past three decades, but better similarity coefficient measures are required. The decision-making process in a manufacturing system often involves uncertainties and ambiguities. Under such circumstances, fuzzy methodologies have proved to be effective tools for taking fuzziness into consideration. In this paper, we use fuzzy cluster analysis to form part-families and assign parts to existing part-families. We have established a new approach to convert a fuzzy clustering matrix into a zero-one incidence matrix. We have also developed a new similarity coefficient measure and this coefficient measure is used to form a part-family. A mathemat-ical model that uses this similarity coefficient for solving optimally the part-family formation problems in cellular manufacturing is developed. Finally, it is compared with other models by giving an illustration with a numerical example.     

An integrated fuzzy DEA–fuzzy C-means–simulation for optimization of operator allocation in cellular manufacturing systems

This paper presents an integrated fuzzy data envelopment analysis (FDEA), fuzzy C-means and computer simulation for optimization of operator allocation in cellular manufacturing systems (CMS). This is a challenging issue in flexible manufacturing systems in general and in CMS in particular. A computer simulation model, which considers various operators layout, is developed. For considering more information from computer simulation report, the output data is fuzzified. FDEA is utilized to assess simulation alternatives in various levels of uncertainty. In addition, FDEA ranking of decision-making units are clustered by fuzzy C-means method. Each of the clusters indicates a degree of desirability for operator allocation. Previous studies only utilize multivariate analysis methods and simulation, whereas this study uses an integrated simulation, fuzzy DEA, fuzzy C-means, and fuzzy indicators. Furthermore, previous CMS studies consider only one type of product, whereas this study considers multiproduct for CMS modeling through simulation. Moreover, more robust CMS assessment indicators are used in the proposed model. A practical case study illustrates the effectiveness and superiority of the proposed methodology. In addition, we compared the results of U shape with other production types, namely spiral, straight, L, W, zigzag, and Z. Moreover, we show that it dominates the other production types.     

An integrated design methodology based on the use of group AHP-DEA approach for measuring lean tools efficiency with undesirable output

The selection of lean tools is one of the crucial factors for decision makers and practitioners in a competitive environment. A few efforts have been made based on problem selection. Conversely, numerical studies have been done on analytical hierarchy process (AHP)–data envelopment analysis (DEA) as well as DEA-undesirable variables separately. Thus, there is a shortage of lean practitioners as well as the methods involved. The present research aims at integrating AHP and DEA with desirable and undesirable factors to evaluate the lean tools and techniques and to rank the aspect of efficacy. We suggest a logical procedure to measure the efficacy of lean tools on leanness and to prioritize them as decision makers. In this extensive research, we apply the integrated multicriteria decision-making approach, including the hybrid groups AHP and DEA models with desirable and undesirable variables, to assess the relative efficiency of lean manufacturing tools and techniques. Case studies are used to demonstrate the lean implementation in companies while being validated by a panel of experts. The integration of these approaches has created synergy and shown to be even more powerful. Thus, the proposed integrated AHP-DEA model can evaluate and rank different alternatives while considering desirable and undesirable variables in the production processes.     

航空制造企业知识管理水平的模糊综合评价方法

在分析航空制造企业中知识资源的构成和知识管理现状的基础上,建立了评价航空制造企业知识管理水平的多层次综合评价指标体系,运用基于三角模糊数的模糊层次分析法来评价航空制造企业的知识管理水平,并给出了方法的具体步骤.该评价方法易于操作,适用于被评价对象的性能无法具体量化、指标权重不易判断的多层次指标综合评价问题.最后通过算例给出了方法的应用.     

A fuzzy DEMATEL-based solution approach for facility layout problem: a case study

Facility layout in production systems is a difficult activity since both qualitative and quantitative factors affect the location decision, and also influence and causal relationship between these factors should be determined for a better location. In this respect, it is demonstrated in this study that fuzzy decision-making trial and evaluation laboratory (fuzzy DEMATEL) method can effectively be used in handling facility layout problems in practice. The qualitative factors that described by linguistic terms can be taken into account through fuzzy structure of the method. Considering this, a fuzzy DEMATEL-based solution approach for facility layout problem is proposed in this study. The proposed approach takes into account both qualitative and quantitative location factors. To address the need in practice, six important location factors are considered in this study. These are material flow, information flow, personnel flow, equipment flow, environmental condition, and supervision of personnel. This study differs from the previous works in that it applies fuzzy DEMATEL method to facility layout problem. To explore the viability of the proposed approach, a real world problem in a machinery industry firm is handled.     

敏捷制造动态联盟盟员的重组优化方法

面向制造企业提出一种敏捷制造动态联盟盟员的重组优化方法，它克服了传统模糊评价方法评价趋于均匀化，易造成决策困难的缺点。     

Decision model for country site selection of overseas clothing plants

Clothing manufacturers’ direct investment and joint ventures in developing regions have grown rapidly in the last few decades. An inappropriate decision on site selection can cause adverse affects on productivity and increase manufacturing and logistical costs. Manufacturers often face with difficulties during the decision-making process, due to vague and subjective considerations. The process is hampered with variables that cannot be represented in terms of objective values, such as country risk and community facilities. The decision on plant location thus relies mostly on the subjective intuition and assessment of the manufacturer. This paper explains the development of a decision-making model for a clothing plant location, using the feed-forward neural network with an error back-propagation (EBP) learning algorithm and a fuzzy analytical hierarchy process (FAHP). Significant variables in the selection of a clothing plant location will be identified and input into the proposed decision-making model. A suitability index was computed for each site. The sites with higher suitability indices were more appropriate for the establishment of a clothing plant. It was also identified that those variables considered on plant location with lower evaluation weights can be neglected without affecting the prediction accuracy of the proposed decision model .