Search results

Continuous process improvement is a hard problem, especially in high variety/low volume environments due to the complex interrelationships between processes. The purpose of this paper is to address the process improvement issues by simultaneously investigating the job sequencing and buffer size optimization problems.

This paper proposes a continuous process improvement implementation framework using a modified genetic algorithm (GA) and discrete event simulation to achieve multi-objective optimization. The proposed combinatorial optimization module combines the problem of job sequencing and buffer size optimization under a generic process improvement framework, where lead time and total inventory holding cost are used as two combinatorial optimization objectives. The proposed approach uses the discrete event simulation to mimic the manufacturing environment, the constraints imposed by the real environment and the different levels of variability associated with the resources.

Compared to existing evolutionary algorithm-based methods, the proposed framework considers the interrelationship between succeeding and preceding processes and the variability induced by both job sequence and buffer size problems on each other. A computational analysis shows significant improvement by applying the proposed framework.

Significant body of work exists in the area of continuous process improvement, discrete event simulation and GAs, a little work has been found where GAs and discrete event simulation are used together to implement continuous process improvement as an iterative approach. Also, a modified GA simultaneously addresses the job sequencing and buffer size optimization problems by considering the interrelationships and the effect of variability due to both on each other.

The purpose of this paper is to model the choice parameters for selection of third party logistics service providers in global lead logistics provider (LLP) environments.

Analytical hierarchy process (AHP) modeling has been carried out after questionnaire‐based survey, results of which were moderated with inputs from experts from industry and academics.

The findings of this study revealed the under lying sub‐parameters which come into play while rating/choosing or evaluating service providers in the global LLP situations of today.

The number of service providers, selection criteria and the number of members of the AHP assessment team have been identified as some of the limitations of the present work.

The study has significant practical implications for the service providers and for the organizations which have to choose them. The fourth party logistics scenario entails this choice to be made by the LLP.

This paper deals with inputs from the Indian LLPs and the Indian service providers. With India emerging as the second most important outsourcing destination after China, the assessment of parameters specific to this country while modeling is of practical importance to LLPs beyond the political boundaries of India also.

The purpose of this paper is to identify the key enabler for total productive maintenance (TPM) implementation in Indian small and medium enterprises (SMEs) by using graph theoretic approach (GTA). There are certain enablers for TPM implementation which helps the organization to implement it successfully. It is very essential to identify the nature and impact of these key enablers.

A large number of the enablers (27) have identified for TPM implementation in Indian SMEs from the available literature, questionnaire survey and expert opinion. These TPM enablers have categorized into six major categories.

In this research work, the intensity of identifying enablers has been calculated to show their impact or influence in TPM implementation. The value of intensity of TPM enablers shows the role or impact of individual enabler in the implementation of TPM in Indian SMEs.

This study provides an easy-to-use methodology for the practical decision makers in the manufacturing industry to improve their performance by implementing TPM in Indian SMEs. A detailed methodology has prepared to identify the enablers for TPM implementation in Indian SMEs by using GTA. This study also explains that how to check the feasibility of an organization to implement TPM in Indian SMEs successfully.

TPM is an improvement concept which holds the potential to improve manufacturing organizations, but its implementation is not easy in Indian SMEs. The reason behind the unsuccessful implementation of TPM in most of the organizations is the ignorance of impact of innumerable enablers and barriers.

The purpose of this paper is to review the literature on total productive maintenance (TPM) implementation practice to present an overview of TPM implementation practices adopted by various manufacturing organizations and suggest possible gaps from researchers and practitioner’s point of view. This study tries to identify the best strategy for improving competitiveness of small and medium enterprises (SMEs) in globalized market and evaluates TPM implementation practice in SMEs.

The objective of this paper is to study the role of TPM program in context of Indian industries either from SMEs to large-scale industries. The approach has been directed toward justification of TPM implementation practice for its support to competitive manufacturing in the context of Indian manufacturing industries.

TPM implementation improves productivity and working efficiency of employees and also improves equipment effectiveness and a positive inclination toward company is registered. Therefore, equipment maintenance is an indispensable function in a manufacturing enterprise. In this highly competitive environment, manufacturing organizations should consider maintenance function as a potential source for cost savings and competitive advantage. SMEs must be considered as an engine for economic growth all over the world (Singh et al., 2008). A total of 148 papers related to TPM implementation in large-scale industries and SMEs were collected, analyzed and classified on the basis of their applications, broadly into large industry and SMEs and further divided into Indian and Non-Indian, then case study, implementation, model, literature review, maintenance, service, etc. This classification has clearly shows that SMEs are in a need to adopt TPM implementation practice to compete in this global market and changing requirements of large industries. Maintenance is an indispensable function in a manufacturing enterprise. In this highly competitive environment, manufacturing organizations must be considered maintenance function as a potential source for cost savings and competitive advantage. Singh et al. (2008) have concluded that SMEs must be considered as an engine for economic growth of all over the world. Following are the objectives of this study: to suggest a classification of available literature on TPM implementation; to identify the need of TPM implementation in SMEs; to identify critical observations on each category of classification; to identify the potential of SMEs in India; to identify emerging trends of TPM implementation in India; to suggest directions for future researchers in the field of TPM implementation on the basis of above mention points; and to consolidate all available literature on TPM implementation practice.

The challenges of stiff competition and the drive for profits are forcing the organizations to implement various productivity improvement efforts to meet the challenges posed by ever-changing market demands. In the dynamic and highly challenging environment, reliable manufacturing equipment is regarded as the major contributor to the performance and profitability of manufacturing systems.

In this dynamic world, importance of SMEs in the growth of the nation needs more attention of researchers and industrialists. After the globalization of market, SMEs have got many opportunities to work in integration with large-scale organizations. All the organizations from SMEs to large-scale industries can adopt effective and efficient maintenance strategies such as condition-based maintenance, reliability-centered maintenance and TPM over the traditional firefighting reactive maintenance approaches (Sharma et al., 2005).

In our view, this paper clearly identifies implications for research which will be useful for society. The gap discussed by authors needs to be addressed by future researchers.

This implementation strategy can help to save huge amounts of time, money and other useful resources in dealing with reliability, availability, maintainability and performance issues. On the basis of available literature, it can be understood that SMEs should change their maintenance strategies to cope up with global competition so that a lot of resources can be utilized in a better direction.

The impact of COVID-19 has caused a recession in economies all over the world. In this context, the current study aims to analyze the prevailing economic scenario using a machine learning approach and suggest sustainable measures to recover the global economy taking the case of Make in India (MII) initiative of developing the economy as a base for the study.

A well-known topic modeling technique – Latent Dirichlet allocation (LDA) algorithm has been employed to extract useful information characterizing the existing state of selected sectors under the MII initiative alongside catalytic policies that have been implemented for the same. The textual data acts as the base of the study upon which suggestions are provided.

The findings obtained suggest that digital transformation will play a key role in concerned sectors to optimize the performance of manufacturing organizations. Additionally, inter-relationship between Key Performance Indicators for the economy's revival is crucial for effective utilization of foreign direct investment resources.

The novel efforts to utilize MII initiative as a case present crucial information which can be used by policy makers and various other stakeholders across the globe to enhance decision-making and draft legislation across different sectors to empower the economy.

The study presents a novel approach to utilize the MII initiative by identifying important measures for crucial sectors and associated policies that have been presented by employing a text mining approach which in itself makes it unique in its contribution to research literature.

The purpose of this paper is to introduce mobile maintenance a new concept of total productive maintenance (TPM) implementation practice, especially in small and medium scale enterprises (SMEs). This study tries to introduce this new concept for SMEs in SMEs to help traditional maintenance program which is already available in particular industries.

The approach is to study the role of mobile maintenance (a part of TPM program) in context of Indian industries either from small and medium scale to large scale industries through overall equipment effectiveness (OEE).

Researchers evolutes a new maintenance concept of TPM implementation practice as mobile maintenance concept in SMEs for enhancing OEE of equipments to improve competitiveness of SMEs in a globalized market. This mobile maintenance strategy can reduce major breakdowns, setup and adjustment losses and improve productivity, product quality and OEE of equipments.

In the dynamic and highly challenging environment, reliable manufacturing equipments are regarded as the major contributor to the performance and profitability of manufacturing systems. A researcher has found that some SMEs of Banmore industrial areas is also using mobile maintenance and preventive maintenance along with traditional maintenance process and getting improvements in the maintenance process as well as machine reliability and OEE of equipments. After the globalization of market, SMEs has got many opportunities to work on integration with large-scale organizations.

It will be very benefitted for the Indian SMEs. SMEs can improve machine availability and OEE by implementing this mobile maintenance concept especially in SMEs.

The purpose of this paper is to determine the criteria weights of outsourcing and their key role in ranking outsourcing suppliers.

A new hybrid multi-criteria decision-making approach merges three tools, namely, decision making trial and evaluation (DEMATLE), fuzzy analytic network process (FANP) and ordinal/cardinal data envelopment analysis (DEA) model. Afterwards, experts’ opinions were gathered from a Pipe and Fittings company. Finally, their opinions were incorporated in three-stage approach for outsourcing suppliers’ selection.

The findings of this study show that among the selective criteria for outsourcing, business development, focus on basic activities and order delays are the three most important criteria. Also, the proposed approach ranks suppliers to facilitate decision making for selection.

The number of suppliers, selection criteria and the number of members of the respondents’ team have been identified as some of the limitations of the present study.

The study has significant and practical implications for the managers and for the organizations which have to choose top suppliers, particularly in the case of dealing with numerous and qualitative/quantitative criteria.

This paper proposed a new three-stage approach that incorporates outputs of previous as inputs of next stage to increasing results accuracy. Also, it showed that by incorporating results of FANP method into DEA model, key role of experts’ opinions as a qualitative and quantitative criteria can be caused by increasing flexibility of decision process.

This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on developing countries like Nigeria. The research identifies barriers to this integration and suggests solutions, intending to provide practical insights for improving operational efficiency in the O&G sector.

The study commenced with an exhaustive review of extant literature to identify existing barriers to I4.0 implementation and contextualise the study. Subsequent to this foundational step, primary data are gathered through the administration of carefully constructed questionnaires targeted at professionals specialised in maintenance within the upstream O&G sector. A semi-structured interview was also conducted to elicit more nuanced, contextual insights from these professionals. Analytically, the collected data were subjected to descriptive statistical methods for summarisation and interpretation with a measurement model to define the relationships between observed variables and latent construct. Moreover, the Relative Importance Index was utilised to systematically prioritise and rank the key barriers to I4.0 integration to CBM within the upstream O&G upstream sector.

The most ranked obstacles in integrating I4.0 technologies to the CBM strategy in the O&G industry are lack of budget and finance, limited engineering and technological resources, lack of support from executives and leaders of the organisations and lack of competence. Even though the journey of digitalisation has commenced in the O&G industry, there are limited studies in this area.

The study serves as both an academic cornerstone and a practical guide for the operational integration of I4.0 technologies within Nigeria's O&G upstream sector. Specifically, it provides an exhaustive analysis of the obstacles impeding effective incorporation into CBM practices. Additionally, the study contributes actionable insights for industry stakeholders to enhance overall performance and achieve key performance indices (KPIs).