Journal of Industrial Engineering and Management 

About: Journal of Industrial Engineering and Management is an academic journal published by OmniaScience. The journal publishes majorly in the area(s): Supply chain & Supply chain management. It has an ISSN identifier of 2013-0953. It is also open access. Over the lifetime, 752 publications have been published receiving 10910 citations. The journal is also known as: JIEM.

Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing

Abstract: Purpose: Lean Manufacturing is widely regarded as a potential methodology to improve productivity and decrease costs in manufacturing organisations. The success of lean manufacturing demands consistent and conscious efforts from the organisation, and has to overcome several hindrances. Industry 4.0 makes a factory smart by applying advanced information and communication systems and future-oriented technologies. This paper analyses the incompletely perceived link between Industry 4.0 and lean manufacturing, and investigates whether Industry 4.0 is capable of implementing lean. Executing Industry 4.0 is a cost-intensive operation, and is met with reluctance from several manufacturers. This research also provides an important insight into manufacturers’ dilemma as to whether they can commit into Industry 4.0, considering the investment required and unperceived benefits. Design/methodology/approach: Lean manufacturing is first defined and different dimensions of lean are presented. Then Industry 4.0 is defined followed by representing its current status in Germany. The barriers for implementation of lean are analysed from the perspective of integration of resources. Literatures associated with Industry 4.0 are studied and suitable solution principles are identified to solve the abovementioned barriers of implementing lean. Findings: It is identified that researches and publications in the field of Industry 4.0 held answers to overcome the barriers of implementation of lean manufacturing. These potential solution principles prove the hypothesis that Industry 4.0 is indeed capable of implementing lean. It uncovers the fact that committing into Industry 4.0 makes a factory lean besides being smart. Originality/value: Individual researches have been done in various technologies allied with Industry 4.0, but the potential to execute lean manufacturing was not completely perceived. This paper bridges the gap between these two realms, and identifies exactly which aspects of Industry 4.0 contribute towards respective dimensions of lean manufacturing.

Barriers to implement green supply chain management in automobile industry using interpretive structural modeling technique: An Indian perspective

Abstract: Purpose : Green Supply Chain Management (GSCM) has received growing attention in the last few years. Most of the automobile industries are setting up their own manufacturing plants in competitive Indian market. Due to public awareness, economic, environmental or legislative reasons, the requirement of GSCM has increased. In this context, this study aims to develop a structural model of the barriers to implement GSCM in Indian automobile industry. Design/methodology/approach: We have identified various barriers and contextual relationships among the identified barriers. Classification of barriers has been carried out based upon dependence and driving power with the help of MICMAC analysis. In addition to this, a structural model of barriers to implement GSCM in Indian automobile industry has also been put forward using Interpretive Structural Modeling (ISM) technique. Findings: Eleven numbers of relevant barriers have been identified from literature and subsequent discussions with experts from academia and industry. Out of which, five numbers of barriers have been identified as dependent variables; three number of barriers have been identified as the driver variables and three number of barriers have been identified as the linkage variables. No barrier has been identified as autonomous variable. Four barriers have been identified as top level barriers and one bottom level barrier. Removal of these barriers has also been discussed. Research limitations/implications: A hypothetical model of these barriers has been developed based upon experts’ opinions. The conclusions so drawn may be further modified to apply in real situation problem. Practical implications: Clear understanding of these barriers will help organizations to prioritize better and manage their resources in an efficient and effective way. Originality/value: Through this paper we contribute to identify the barriers to implement GSCM in Indian automobile industry and to prioritize them. The structured model developed will help to understand interdependence of the barriers. This paper also suggests the removal of these barriers.

Industrial revolution - industry 4.0: Are German manufacturing SMEs the first victims of this revolution?

Abstract: Purpose : Industry 4.0 represents a special challenge for businesses in general and for SMEs in particular. The study at hand will examine companies´ awareness, readiness and capability to meet this challenge taking into account the special role of SMEs. Methodology: The results of nine studies dealing with this range of topics are examined in the framework of a systematic review and compared with regard to the objective of the study at hand. Findings: The review showed that, as a rule, there is an awareness concerning the relevance of the topic. The readiness and the capability to meet this challenge exist in parts; however, they strongly depend on the enterprise size. The smaller SMEs are, the higher the risk that they will become victims instead of beneficiaries of this revolution. Originality/value : Considering different studies concerning Industry 4.0 the article gives an insight into the dependence of the Industry 4.0 readiness in reference to the company size. This deepens the knowledge in adaption deficits German SME still have and opens different approaches for further research and action plans.

Three stage maturity model in SME’s toward industry 4.0

Abstract: Purpose: To address the challenges regarding the concept of Industry 4.0 and the diversification methodology and based on the strategic guidance towards Industry 4.0, we propose a process model as a guiding framework for Industry 4.0 collaborative diversification vision, strategy and action building. In this paper we suggest a stage process model to guide and train companies to identify new opportunities for diversification within Industry 4.0. Systematically carrying out the stages will take a company to their individual specific vision and collaborative vision between different companies in the Industry 4.0 scenario. Design/methodology/approach: This new collaborative diversification methodology involves industry within the pilot program; from the diversification and capacity assessment analysis of the company`s profile, skills and technologies that dominates, to identify the diversification opportunity map and its business modeling within the Industry 4.0 paradigm. Findings: The application of maturity models to the Industry 4.0 may help organizations to integrate this methodology into their culture. Results show a real need for guided support in developing a company-specific Industry 4.0 vision and specific project planning. Originality/value: Industry 4.0 promotes a vision where recent developments in information technology are expected to enable entirely new forms of cooperative engineering and manufacturing. The vision of industry 4.0 describes a whole new approach to business operations, and especially the production industries. To address the challenges regarding the concept of Industry 4.0 and the diversification methodology discussed above, and based on the strategic guidance towards Industry 4.0, we propose a unique process model as a guiding framework for Industry 4.0 collaborative diversification vision, strategy and action building.

Optimization of a truck-drone in tandem delivery network using K-means and genetic algorithm

Abstract: Purpose: The purpose of this paper is to investigate the effectiveness of implementing unmanned aerial delivery vehicles in delivery networks. We investigate the notion of the reduced overall delivery time, energy, and costs for a truck-drone network by comparing the in-tandem system with a stand-alone delivery effort. The objectives are (1) to investigate the time, energy, and costs associated to a truck-drone delivery network compared to standalone truck or drone, (2) to propose an optimization algorithm that determines the optimal number of launch sites and locations given delivery requirements, and drones per truck, (3) to develop mathematical formulations for closed form estimations for the optimal number of launch locations, optimal total time, as well as the associated cost for the system. Design/methodology/approach: The design of the algorithm herein computes the minimal time of delivery utilizing K-means clustering to find launch locations, as well as a genetic algorithm to solve the truck route as a traveling salesmen problem (TSP). The optimal solution is determined by finding the minimum cost associated to the parabolic convex cost function. The optimal min-cost is determined by finding the most efficient launch locations using K-means algorithms to determine launch locations and a genetic algorithm to determine truck route between those launch locations. Findings: Results show improvements with in-tandem delivery efforts as opposed to standalone systems. Further, multiple drones per truck are more optimal and contribute to savings in both energy and time. For this, we sampled various initialization variables to derive closed form mathematical solutions for the problem. Originality/value: Ultimately, this provides the necessary analysis of an integrated truck-drone delivery system which could be implemented by a company in order to maximize deliveries while minimizing time and energy. Closed-form mathematical solutions can be used as close estimators for final costs and time.