Economic and Environmental Assessment of Spare Parts Production Using Additive Manufacturing

This chapter aims to investigate the potential economic and environmental sustainability outcomes of additive manufacturing (AM) for spare parts logistics. System dynamic simulation was conducted to analyze the sustainability of producing a spare part used in a railways subsystem using a particular additive manufacturing (AM) technology (i.e., selective laser sintering [SLS]) compared to producing it using injection molding. The results of the simulation showed that using SLS for the chosen part is superior to the conventional one in terms of total variable costs as well as for carbon footprint. Compared to the conventional supply chain, for the AM supply chain, the costs of the supplier reduces by 46%, that of the railways company reduces by 71%, while the overall supply chain costs reduce by 61.9%. The carbon emissions in the AM supply chain marginally reduces by 2.89% compared to the conventional supply chain.

Exploring the Blockchain Technology Application in the Chinese New Retail Business Model

While the new retail is revolutionizing retailing in China, the supply chain of the new retail has a few problems or potential risks which will decrease the customer satisfaction level. However, the implementation of one of the cutting-edge technologies—the blockchain—can revolutionize the supply chain of the new retail in China. This qualitative piece uses multiple interviews to find out the specific outcomes blockchain will make for the supply chain of the new retail in China. The major contribution is to fill the gap of the academic literature as well as the business application and such as the new retail in China to increase supply chain security and efficiency with blockchain.

Supply and Demand Management During Industrial Evolutions

The aim of this chapter is to understand the status quo of academic research on demand and supply management in terms of cause and mitigation strategies during the third industrial revolution and estimate the scope in the fourth industrial revolution. The chapter uses a systematic literature review approach to classify the past studies published in the International Journal of Production Research during the third industrial revolution based on cause and mitigation strategic framework. Similarly, the study estimates the scope in future by brainstorming academicians and practitioners using Q-methodology. This analysis reveals that dependence on technology will simplify tracking of transit inventory and real-time sharing transparency and continuous updating will simplify demand forecasting.

An Exploratory Study on Blockchain Application in a Food Processing Supply Chain to Reduce Waste

This chapter aims to explore the feasibility of using blockchain in the beef supply chain to reduce waste. A mono-method, qualitative, inductive, single case study approach was taken on a cross-sectional scale from June 2018 to August 2018, with two individuals interviewed: a beef and a blockchain expert. The case study also involved observations, a field visit, and other secondary source data. Beef is a high demand, valuable food product with a limited shelf life. By using blockchain in conjunction with RFID and sensor technologies, farming and processing stages in the beef supply chain can be streamlined. Firstly, using the technology to monitor the animals on the farm and during transportation can reduce the amount of water and energy wasted. Secondly, blockchain can be used to establish exactly when and where the meat is cut and packaged, improving the accuracy of information between supply chain entities, resulting in improved inventory management, specifically more accurate delivery times and lengthened product shelf lives.

Evaluation of Influence of Principles Involved in Industry 4.0 Over Coal Industries Using TISM

Coal is the major source of energy in the world. But, the process of extraction and use of coal has adverse effects on the environment. In this chapter, the authors try to reduce these effects by considering the principles and technologies involved in Industry 4.0, also known as the Fourth Industrial Revolution. From a few expert reviews and research works, eight crucial factors were taken into account and were analyzed. The eight factors are consumer, water resources, smart transportation, smart factory, smart grid, smart mining, smart home, and renewable energy. The analysis has been made using the total interpretive structural modeling (TISM) method. The model distinctly demonstrates the influence of the principles of Industry 4.0 over coal industries. This chapter also aims to pave the way for future research and tries to contribute towards the sustainable extraction and usage of coal in energy industries. Consumer plays the most influential role in this regard.

Autonomous Vehicle in Industrial Logistics Application

Rapid technological advances have revolutionized the industrial sector. In the global market, it is necessary to consider the new paradigm of Industry 4.0 that presents a lot of features in the industrial logistics application. It has been seen through literature that innovation management practices enable companies to compete within the autonomous and connected vehicle market and is considered as an emerging and competitive differentiator towards the growth of the product and that of meeting customer demands within the changing markets. The first case study explores the integration of GPS and GLONASS signals in AGV for localization and navigation of customer destination and materials in the indoor and outdoor environment. The second case study implemented in obstacle environment that recognized the obstacle in front of the robot and also identified the dimension of the obstacle size, length, width, circumference, height, and distance from a robot. The strength and disadvantages of the system are discussed in the logistical application and future outlines are provided.

The Challenges and Solutions of Cybersecurity Among Malaysian Companies

The objective of this chapter is to analyze the challenges faced by Malaysian companies in cybersecurity and to determine solution for Malaysian companies to overcome challenges in cybersecurity. The data were collected from the expert people in cybersecurity fields using interview sessions. The finding confirmed that the awareness and budget are very important in other to implement the element of cybersecurity in the company. Cybersecurity is good and desired as a protection for an organization in developing strategic planning to gain more profitability and increase the productivity of goods and services. This research will be beneficial for the organization because it will provide the solution for the company to overcome the cybersecurity issues. From this research, an organization can have potential to enhance competitiveness and understand the problem occur, then do the improvement by implementing cybersecurity.

Factors Influencing Blockchain Diffusion in the Supply Chain

The literature concerning supply chain management (SCM) and blockchain integration is scarce, and organizations and decision makers still have a limited knowledge about blockchain solution diffusion in SCM. Under these circumstances, studies aimed to improving the understanding of the main blockchain diffusion factors are fundamental. This chapter is a contribution to bridging such gaps, as it aims to unlock the driving factors of blockchain diffusion in the SCM environment. Based on the emerging literature on blockchain, supply chain management, expectancy theory, and diffusion of innovations, a model was developed and validated, considering data from India's supply chain management professionals. The data was analyzed using partial least square structural equation modeling (PLS-SEM). The results indicated that IT deployment capability, compatibility, and trading partner pressure are factors that affect blockchain diffusion significantly. Also, the results bring essential managerial and theoretical implications regarding the blockchain diffusion in the SCM.

Smart Make-to-Order Production in a Flow Shop Environment for Industry 4.0

The permutation flow shop scheduling problem is one of the popular problems in operations research due to its complexity and also its practical applications in industries. With the fourth generation industrial revolution, decisional aspects in make to order flow shop environment needs to be decentralized and autonomous. One of the aspects is to consider a real-time or dynamic production environment where customers place orders into the system dynamically and the decision maker has to decide whether the order can be accepted considering the available production capacity and how to schedule the jobs of an accepted order. To answer these research questions, in this chapter, the authors introduce a new decision-making, real-time strategy intended to yield flexible and efficient flow shop production schedules with and without setup conditions, Numerical experiments based on realistic problem scenarios show the superiority of the proposed real-time approach over traditional right shifting approaches.

Multi-Objective Optimization of Economic and Environmental Aspects of a Three-Echelon Supply Chain

It is very relevant in today's competitive world for suppliers to ensure that customer-demanded products are made available. Customers expect to obtain a product that has benefits and are available within an acceptable price and time. It is necessary for companies to optimally use their ability to satisfy customers' specified needs. Researchers and industries are working on developing green supply chain concept in the last few years due to environmental concerns. The objective of this chapter is to propose a three-echelon supply chain model that optimizes economic and environmental objectives simultaneously. The objectives considered are minimizing the total supply chain cost and minimizing CO2 emission of the supply chain network. The proposed model falls into NP-hard category. Multi-objective genetic algorithm is proposed to solve the proposed model and illustration is provided to explain the use of the proposed model. A procedure that could be followed to find the best possible solution based on user's choice among the Pareto front solutions is also explained.