Country-specific barriers to implementing lean production systems in China

This thesis examines barriers to the implementation of Lean production systems in China. The aim is to evaluate how implementation barriers affect a Lean production system, and whether they can be explained by Chinese national context factors. The thesis also aims to investigate the mechanisms by which such context factors influence the barriers. A socio-technical systems (STS) perspective is taken to interpret the relative importance of, and the interplay between, the social and the technical barriers to Lean implementation in China. To achieve the aims of the study, a multiple case study approach was chosen. I collected data at two Chinese plants of a globally-operating German automotive supplier in Suzhou and Changsha. As the main method of data collection, I conducted sixty qualitative interviews with Chinese and Western employees during a two month research trip to China. Using an iterative procedure of data collection and analysis, I developed a model that captures barriers to implementing Lean in China, the effects of these barriers on the production system, and influential context factors. Based on respondents perceptions, I identify six main implementation barriers, namely: High employee turnover , Weak supplier performance , Market conditions , Lack of Lean knowledge , Intercultural communication , and Work styles . The analysis highlights the effects of the barriers on specific elements of the Lean production system, and mechanisms by which the context factors influence the barriers. By exploring these mechanisms, I found strong evidence that Chinese context factors act as root causes or catalysts for the implementation barriers. The findings are corroborated through a comparison of the results obtained from the two locations in China, reports by Western and Chinese employees, and respondents at different hierarchical levels of the organisation. Through the Lean implementation model, this research contributes to the literatures on international Lean manufacturing and socio-technical systems. The study is the first to provide detailed empirical evidence of six main barriers, and to describe thoroughly why each barrier was a burden for Lean. The thesis also contributes to the Lean literature by demonstrating how the national context of China can create barriers and therefore play a significant role when implementing Lean in China. The central claim of the study is therefore that implementation barriers do exist in China and that a greater focus on these barriers is required in order to gain a better understanding of Lean implementation in this context. With regard to STS theory, the study highlights that the main perceived barriers to Lean implementation were situated within the social sub-system of Lean, and that some aspects of the barriers were created through a lack of joint optimisation of the social and the technical sub-system. The study therefore shows that STS theory is applicable to the context of Lean systems, and that it facilitates our understanding of barriers to the socio-technical Lean system. The study yields recommendations on managerial strategies for implementing Lean production in China, regarding people management as well as the adjustment of manufacturing facilities. A consideration of the national context can help practitioners to fully understand the causes of implementation barriers in China and, through this, to overcome these barriers. The thesis is concluded by reflecting on its limitations and suggestions for future research

After sales supply chain risk management.

Lean supply chains with cost optimized production and logistics processes in the automotive industry have become a benchmark for other industries. Short delivery times, low inventories and high availability are parameters which assume a robust supply chain. In industrial practice we see, however, that in the After Sales business particularly related to the supply of automotive spare parts, that there are always unforeseen delays in delivery. In order to avoid service level losses on the focal firm level due to missing parts it is necessary to understand the risk structure on the supplier side. For this reason, a risk model for the After Sales inbound SC is developed through this work. Based on an extensive analysis of delivery data a central risk size was derived. Comprehensively researched SC risks are supplemented by After Sales specific risks derived through an empirical supplier survey. A reference network, which is methodologically based on the Bayesian theorem, to control the dynamic relationships was developed. The developed risk model allows for the identification of proactive and reactive measures by top-down and bottom-up analyzes to make lean supply chains for after sales requirements in the best cases robust and resilient. A big advantage of the developed model is not only the ability to quantify the cause and effect of supply chain risks but also to describe the constantly changing risk environment of the supply chain through continuous belief updates within the model. The risk analysis in the developed model potentially reduces the delivery delay of spare parts by 65 percent and diminishes the buffer stock value by 50 percent. To achieve such improvements in the real world organizations must be able to implement measures in explicit SC risk clusters for sustainable supply chain performance and inventory management. Improvements in the internal supplier processes, due to risks like prioritized series supply, or inappropriate after sales supply strategies are necessary. Utilizing the developed After Sales Risk Management Model (ASRIM) organizations will be able to implement proactive risk mitigation strategies, facilitating agile SC performance, while simultaneously reducing buffer stocks

Application of Multi-Objective Optimization Based on Genetic Algorithm for Sustainable Strategic Supplier Selection under Fuzzy Environment

Purpose: The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM). Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem. Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value measure (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multiobjective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis. Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability. Research limitations/implications: Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world problems. A detailed comparative analysis by using other algorithms is necessary for solving similar problems of agriculture, pharmaceutical, chemicals and services sectors in future. Practical implications: It can help the decision makers for ordering to different supplier for managing supply chain performance in efficient and effective manner. From the procurement and engineering perspectives, minimizing cost, sustaining the quality level and meeting production time line is the main consideration for selecting the supplier. Empirically, this can facilitate engineers to reduce production costs and at the same time improve the product quality. Originality/value: In this paper, we developed a novel multi-objective programming model based on genetic algorithm to select sustainable strategic supplier (SSSS) under fuzzy environment. The algorithm was tested and applied to solve a real case of textile sector in Pakistan. The experimental results and comparative sensitivity analysis illustrate the effectiveness of our proposed model.Peer Reviewe

Manufacturing System Lean Improvement Design Using Discrete Event Simulation

Lean manufacturing (LM) has been used widely in the past for the continuous improvement of existing production systems. A Lean Assessment Tool (LAT) is used for assessing the overall performance of lean practices within a system, while a Discrete Event Simulation (DES) can be used for the optimization of such systems operations. Lean improvements are typically suggested after a LAT has been deployed, but validation of such improvements is rarely carried out. In the present article a methodology is presented that uses DES to model lean practices within a manufacturing system. Lean improvement scenarios are then be simulated and investigated prior to implementation, thereby enabling a systematic design of lean improvements

Leanness and agility as means for improving supply chains. A case study on Egypt

Supply chain management has received greater attention from the academics and the practitioners, however the literature review lacks a comprehensive view for supply chain management practices and how its members should act to contribute to its overall success (Li el at., 2005). In this era, where the business organisations are working in several challenging threats and opportunities, greater attention is given to supply chain management. Nowadays, companies are always searching for means to improve their supply chains. The main aim of this research is to show "how leanness and agility approaches can be used within the same enterprise as complementary means for improving its supply chain". To achieve this research objective, the research has provided an assessment and summarised the literature on the supply chain management, lean thinking and agility thinking including their importance; their definitions; their practices and the relationship between lean and agility. The resulted proposed framework deduced from the literature has been applied in the Egyptian Manufacturing Business to show the relationship between the agility principles, lean principles, entity performance and the successful supply chain

Automation from lean perspective-potentials and challenges

The competitive climate of production and high labour cost, motivate western companies to use technologies like automation as a mean to increase manufacturing competitiveness. On the other hand companies are aware about cost reductive policies like lean production which has shown noticeable achievement, consequently some manufacturers tend to follow such system. In this situation, in order to have lean enterprise, it is vital to find a clear picture of challenges and potentials of implementing automation within a lean environment. So, finding the right level and type of automation becomes vital for companies, and achieving this is not possible without a lean development of automation. The paper presents an overview of automation development from a lean perspective. The focus is on manufacturing and a case study in the automotive industry is presented. Challenges and potentials of automation are pinpointed and some suggestions regarding automation development is given

Measuring the level of lean readiness of the Hong Kong's manufacturing industry

Increasingly competitive business environments have forced manufacturing organisations to continuously seek improvements in their production processes as an alternative to achieve operational excellence. Lean manufacturing principles and techniques based on the elimination waste have been widely used by manufacturing organisations around the world to drive such improvements. The purpose of this paper is to present an empirical study that evaluates the readiness level of the Hong Kong’s manufacturing industry to provide a foundation for the successful implementation and/or sustainment of lean practices. To conduct this study, the paper adapts an assessment framework developed by Al-Najem et al. [16]. Thus, the lean readiness assessment is based on six quality practices (i.e. planning & control; processes; human resources; customer relations; supplier relations; and top management & leadership) related to lean manufacturing. One research question and three hypotheses were formulated and tested using a combination of inferential statics (i.e. Levene’s test and t-test) and descriptive statistics. Data were collected through a survey questionnaire responded by 9 manufacturing organisations with operations in Hong Kong. The findings suggest that the Hong Kong’s manufacturing organisations surveyed do not currently have a well-developed foundation to implement or sustain lean manufacturing. In particular, these organisations present important opportunities to further develop some quality practices such as processes, planning & control, customer relations, supplier relations, human resources, and top management & leadership. The improvement of these quality practices will ensure, according to Al-Najem et al.’s [16] framework, a more effective implementation and sustainment of lean manufacturing in their operations