Application of interpretive structural modelling for analysis of factors influencing lean remanufacturing practices

The contemporary manufacturing scenario witnesses the adoption of lean remanufacturing concepts in a concerted manner. Lean remanufacturing is a newly evolved manufacturing process concerned with manufacturing and remanufacturing of products to effectively utilise available energy and resources, while reducing wastes in the process and thereby increasing efficiency. The advantages include process streamlining coupled with end-of-life decisions. A structural model needs to be developed to clarify the interrelationships among factors influencing lean remanufacturing practices. In this study, interpretive structural modelling method has been used to develop the structural model depicting interrelationships and most dominant and least dominant factors. Twenty factors are being identified based on expert opinion from 35 Indian automotive component remanufacturing organisations. The identified most dominant factors include a strong top management commitment with proper strategy selection, long-term vision and participation and a strong understanding of the current product and process designs. MICMAC analysis has been conducted to categorise the factors. The inferences based on the study have been derived. The novel aspect of this study is that it presents the development of structural model to identify the most dominant factors influencing the implementation of lean remanufacturing principles.     

Analysis of SCF under sales promotional schemes: an application of interpretive structural modelling approach

In the competitive market of today, supply chain flexibility (SCF) plays crucial way to address various supply chain uncertainties. But, in diverse situations, the supply chain needs different types of flexibilities. This paper analyses the flexibility of an automobile supply chain under sales promotional schemes (SPS) to meet the demand uncertainty. Taking the opinion of supply chain experts from automobile original equipment manufacturers (OEM’s), 14 SCF strategies have been identified and then using interpretive structural modelling (ISM) on the conducted survey, their interrelationships are established and a hierarchical model is developed. MICMAC analysis is done to classify the strategies into four categories viz. autonomous, dependent, linkage and independent strategies, which are based on their driving and dependence powers. Sensitivity analysis has been conducted to check the stability of the model. The thorough exposition of the model presents a handful of insights to supply chain managers to know the most important strategies affecting each other. The study helps in bridging the SCF with SPS, a huge gap existing in the literature.     

Estimation of reliability and validity of agility constructs using structural equation modelling

The main objective of this study was to create an agile manufacturing (AM) model and to validate the model using structural equation modelling (SEM). AM concentrates on turbulent market changes and the responsive actions of the manufacturing firm, in terms of process, tooling, material and trained experts. The AM model consists of five major drivers of agility, namely the workforce, manufacturing management, manufacturing strategy, manufacturing technology and organisational structure. After development of the AM model, a questionnaire was prepared and data collected from 30 automotive organisations located in Tamil Nadu, India. After data collection, the SEM approach was used to conduct a statistical validation. The results indicate the validity and reliability of AM constructs.     

Advancing operations management theory using exploratory structural equation modelling techniques

The structural equation modelling (SEM) technique has been touted as a useful tool for tightening links between theoretical and empirical operations management (OM) research. Despite SEM's increasing prominence in the field, leading scholars continue to call for a deeper infusion of theory into empirical OM research. To strengthen ties between theory and analysis in OM research, this study evaluates previous OM applications of SEM and identifies specific ways we can use SEM to advance operations management theory. Through judicious use of SEM techniques, we believe that OM researchers have the opportunity to confirm and extend existing theoretical frameworks. Further, we offer guidance on how to operationalise measurement models such that researchers accurately depict the causality of a construct. To demonstrate how to advance theory, we use an illustrative example of SEM in an OM context based upon data gathered from a survey of over 200 respondents.     

Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies

The current literature claims the direct effects of industry 4.0 technologies (I4?T) on lean manufacturing practices (LMP) and sustainable organisational performance (SOP). LMP are also found to have a positive influence on SOP. However, the integrated effect of I4?T and LMP on SOP has not been empirically investigated. To address this gap, this research study investigates the indirect effects of I4?T on SOP with LMP as the mediating variable; furthermore, it aims to confirm or not the direct effects of I4?T on LMP and SOP. The study is based on data collected from 205 managers, working in 115 manufacturing firms. The findings suggest significant direct and indirect effects of I4?T on SOP and confirm the presence of LMP as a strong mediating variable. The results of the study extend the literature on I4?T by identifying I4?T as an enabler of LMP, leading to enhancement of the SOP. Implications and future research directions for academicians, practitioners, and consultants are provided.     

Application of system dynamics modelling for a sustainable manufacturing system of an Indian automotive component manufacturing organisation: a case study

Clean Technologies and Environmental Policy - Over the last few decades, the manufacturing industry has been a major contributor to pollution and consumes a greater portion of the world´s...     

Determinants of mobile supply chain management system diffusion: a structural equation analysis of manufacturing firms

Mobile supply chain management (SCM) is gaining recognition as a major source of cost reduction and supply chain performance improvement. The current literature related to mobile SCM needs to be extended further in order to provide insights into how manufacturing firms can implement mobile SCM successfully. Specifically, there is a need to provide empirical and systematic analysis of the variables that can explain the various stages of mobile SCM diffusion. A review of recent literature suggests that existing e-supply chain technology adoption literature is not strongly grounded in theory. A theoretical model with six hypotheses was proposed based on the technology–organisation–environment (TOE) framework and innovation diffusion theory (IDT). This study draws its survey responses from a group of manufacturing firms in order to investigate the factors that affect the diffusion of mobile SCM. The results show that the variables derived from TOE and IDT can explain mobile SCM diffusion well. However, interorganisational relationships (IORs) play a crucial role in determining the success of mobile SCM routinisation. This is one of the first known empirical studies on the factors influencing the diffusion of mobile SCM. The results of this study will help decision makers better understand the implementation process of mobile SCM and formulate strategies for successful diffusion of mobile SCM.     

Structural equations modelling for relational analysis of JIT performance in maquiladora sector

This paper analyses the process of implementing a just-in-time (JIT) methodology in maquiladora assembly plants in Mexico, through 20 activities undertaken in the areas of administration, supervision and production. The proposed approach uses a factor analysis of each group of variables (validating their feasibility through an analysis of the correlation matrix) by sections, activities and benefits obtained. A structural equations model is proposed to show how key factors in the success of the implementation of JIT associated with productive activities interrelate with factors linked to benefits. The results forthcoming from the study show that the benefits obtained through the proper administration by senior managers of their powers are directly reflected in the plant’s productivity indices, such as increases in output, quality and the operational flexibility of production systems. Furthermore, a good relationship with and management of suppliers guarantees an acceptable level of control over inventories, regarding both work in process and the end product, and likewise impact upon productivity indices.     

The significance of organizational change management for sustainable competitiveness in manufacturing: exploring the firm archetypes

The successful development and deployment of adequate sustainable manufacturing strategies are still open issues and of utmost interest for research and practice. Guided by this particular challenge, we investigate the significance of organisational change management for sustainable competitiveness in manufacturing. By using six case studies from the Lombardia region in Italy and basing our research on the theoretical constructs of competitive aggressiveness and organisational change, we discover four archetypes of companies that show an increasing sustainable competitiveness with an increasing formalism and persistence in organisational change. Our findings suggest that change management practices are conditional hypothesis for creating competitive advantage through sustainability, and implementation gaps do hinder companies in realising the full potential. The study offers guidance to stakeholders, on how change management actions may potentially affect company performance in the manufacturing sector, as well as providing direction on the impact improved planning and leadership instances can have on the sustainability performance.     

Sectoral dynamics and technological convergence: an evolutionary analysis of eco-innovation in the automotive sector

We know from evolutionary theory that sectoral characteristics are important to innovation. This paper investigates if sectoral characteristics also are important to eco-innovation, a hitherto under-researched theme. We argue that research into possible sectoral patterns in eco-innovation is key to understanding green industrial dynamics and the greening of the economy. This paper investigates to what degree the economy is greening horizontally (sector-wise). Starting with a sectoral case study, we undertake a longitudinal analysis of the breath and strength of the greening of the automotive sector from 1965 to 2012, focusing on powertrain technologies. The empirical analysis is based on patent data amongst big car producers and focuses on identifying changes in two main aspects: (1) the convergence/divergence of firms’ green strategies and technologies within the automotive sector; and (2) the contribution of alternative key green technological trajectories relative to the dominant design. Our findings indicate that the evolution of relative green patenting has followed a positive, linear growth over the last decades with increasing participation of alternative propulsion technologies and increasing convergence of automakers’ strategies towards a diversified portfolio.     

Value-added path of service-oriented manufacturing based on structural equation model: the case of electric car rental for instance

Electric cars foreshadow the future direction of the automotive industry owing to its great potential for environment protection. Electric car rental may be an effective mode to popularise the electric car, before the cost of the electric car can be reduced substantially. To provide the electric car rental service well, the company must understand how consumers value renting an electric car and what they consider to be value-added, which is the main objective of the research. First, the concepts of customer participation (CP), service quality (SERVQUAL) and customer value (CV) are identified. Then, the value-added path structural equation is constructed by exploratory factor analysis and confirmatory factor analysis. Use path coefficient and standard factor loading to identify the value-added paths and key factors in the electric car rental. The results show that CP will improve customer satisfaction and the post-purchase intentions, through the improvements of SERVQUAL and CV and thus realising the added value of the path.     

Adoption of green supply chain management practices and their impact on performance: an exploratory study of Indian manufacturing firms

Research on green supply chain management (GSCM) or sustainable supply chain management (SSCM) has attracted increased attention in recent years. Although GSCM/SSCM has been studied for developed and developing countries, there has been little information about the adoption of GSCM/SSCM practices in India. This article presents one of the earliest surveys on GSCM practices in Indian manufacturing firms. The items for the survey were developed based on the extant literature and feedback from corporates. Some of the major findings of the survey are as follows. We found that the state of adoption of GSCM practices by Indian firms was still in its infancy, the awareness of environmental sustainability was quite low among consumers, and the regulatory framework was also lacking in terms of promoting environmental sustainability. Results of data analysis showed that supplier collaboration for environmental sustainability had a positive impact on environmentally sustainable product design and logistics, which in turn was positively related to competitiveness and economic performance of the firm. We compared the results with the observations made by other researchers for developed and developing countries and provided managerial implications for the government and manufacturers as to what steps need to be taken to generate awareness towards environmental sustainability and facilitate the adoption of GSCM practices among Indian firms to a greater extent. We conclude the paper by indicating directions for future research on GSCM/SSCM.     

预浸料生产中智能控制系统的应用

用近红外光谱技术对无碱布/酚醛预浸料的树脂含量、可溶树脂含量和挥发分含量进行在线检测,通过偏最小二乘方法分别建立标准模型,选择光谱预处理方法和PLS的因子数.用近红外方法和标准方法对未知样品进行分析,通过t检验结果显示两种方法没有显著性的差别,利用该方法可以同时预测三项指标,1分钟之内就可以分析一个样品,没有破坏性.如果质量指标不合格,通过自动控制系统发出指令,及时调节工艺参数.研究表明近红外光谱方法能够十分有效和准确对分析预浸料质量.     

Application of NIR chemometric methods for quantification of the crystalline fraction of warfarin sodium in drug product

Abstract

Monitoring of the physical state of warfarin sodium (WS) in products is essential for minimizing product quality variability in order to ensure consistent clinical performance. This study reports the development of chemometric models for quantifying the crystalline and amorphous fractions of WS in commercial drug products using NIR spectroscopy. Formulations based on commercially available products with different API to excipient ratio were used for the study. For each content, two formulations containing either lactose monohydrate or lactose anhydrous as the predominant formulation excipient were prepared. Two formulations containing either 100% amorphous WS (AWS) or crystalline WS (CWS) were prepared and mixed in various ratios to obtain sample matrices containing AWS/CWS 0–100%. The uniformity of the samples was confirmed by near infrared chemical imaging. Data were mathematically pretreated by multiplicative signal correction and Savitzky–Golay second derivative. Principal component regression and partial least square regression models were developed from mathematically treated data. All the models showed linear trend for amorphous and crystalline fractions of the WS as indicated by correlation and R²?>?0.99 and >0.98, respectively. The models demonstrated good performance parameters with a low-root mean squared error, standard error and bias. The model predicted CWS and AWS contents were in very close agreement with the actual values. The study indicated the utility of NIR chemometric methods in quantification of the crystalline and/or amorphous fraction of WS in its products.     

3D‐based hp‐adaptive first‐order shell finite element for modelling and analysis of complex structures—Part 2: Application to structural analysis

The paper presents a 3D‐based adaptive first‐order shell finite element to be applied to hierarchical modelling and adaptive analysis of complex structures. The main feature of the element is that it is equipped with 3D degrees of freedom, while its mechanical model corresponds to classical first‐order shell theory. Other useful features of the element are its modelling and adaptive capabilities. The element is assigned to hierarchical modelling and hpq‐adaptive analysis of shell parts of complex structures consisting of solid, thick‐ and thin‐shell parts, as well as of transition zones, where h, p and q denote the mesh density parameter and the longitudinal and transverse orders of approximation, respectively. The proposed hp‐adaptive first‐order shell element can be joined with 3D‐based hpq‐adaptive hierarchical shell elements or 3D hpp‐adaptive solid elements by means of the family of 3D‐based hpq/hp‐ or hpp/hp‐adaptive transition elements. The main objective of the first part of our research, presented in the first part of the paper, was to provide non‐standard information on the original parts of the element algorithm. Here we describe the second part of the research, devoted to the methodology and results of the application of the element to various plate and shell problems. The main objective of this part is to verify algorithms of the element and to show its usefulness in modelling and adaptive analysis of shell and plate parts of complex structures. In order to do that, there is a presentation of the results of a comparative analysis of model plate and shell problems using the classical and our elements, and equidistributed and integrated Legendre shape functions. For the plate problem a comparison of the results obtained from the adaptive and non‐adaptive analysis is also included. Additionally, some advantages of the application of our element are shown through a comparative analysis of p‐convergence of the thin plate problem and an adaptive analysis of the exemplary complex structure. Copyright © 2006 John Wiley & Sons, Ltd.