In the second section, the history of the first three Industrial Revolutions and their impact is presented. Another major impact of the First Industrial Revolution was on the economy of the United States.
The Industry 4.0 Framework
The impact of the third industrial revolution in terms of the time of adaptation was overwhelming. In the second half of the 20th century, nuclear energy also took its place at the core of the third industrial revolution (Sentryo 2019).
A review of the Industry 0 Literature
The authors claim that the collaboration between Industry 4.0 and lean production systems adds value to companies. The authors further discuss the fundamental technologies behind Industry 4.0 and the impact of the Internet on manufacturing technologies.
Conclusion and Future Research
2018) reviews the current status of the research in domains of Industry 4.0 and classifies Industry 4.0 research categories. The authors validate the effectiveness of their proposed model using an Industry 4.0-based case study.
SCM in Industry 4.0 Era
- Introduction
- Fundamentals of Logistics: Definitions and Terminology
- Digitalization of Logistics and Challenges in Logistics 4.0 1 Inventory Control Systems (ICS)
- Industry 0, Logistics 0 & Supply Chain 0
- Conclusion and Future Direction
Digitization of logistics and challenges in logistics 4.0 3.1 Inventory control systems (ICS) 3.1 Inventory control systems (ICS). The term "Logistics 4.0" refers to the integration of logistics and the emerging innovations and applications of CPS.
C HAPTER 3
The Internet of Things
As a result of the latest technological improvements, every device eventually becomes "smart" by integrating the Internet. Although IoT is an important component of the Industry 4.0 concept, it is also associated with various new technological improvements such as cyber-physical systems, machine learning, and cloud computing.
Challenges of The Internet of Things
As a result, IoT-related technologies help companies collect, store and analyze big data released by smart devices. Standardization supports the integration process of IoT-related technologies in smart production systems (Trappey et al. 2017).
Changes in Business Models and Production Processes
The integration of IoT-related technologies allows employees to work in safe conditions and increase employee productivity. In particular, the structure of the production systems is completely differentiated from the traditional ones with the integration of IoT-related technologies.
The Effects of The Internet of Things on Supply Chain Management
Proper integration requires close collaboration between companies to increase supply chain efficiency. Supply chain risk can arise from environmental, organizational, and network-related factors, and these factors can strongly influence supply chain structure (Jüttner et al. 2003).
Conclusion
With the advent of Industry 4.0, SC had to implement some changes to keep up with the innovations that Industry 4.0 has brought. Then, the literature review of IoT and Supply Chain in the context of Industry 4.0 is included in Section 4.
Historical Development of the Industrial Revolution and The Emergence of Industry 4.0
With the increase in means of transport, the spread of the industrial revolution to Europe accelerated. Kovacs (2018) analyzed the dark corners of Industry 4.0 development and its effects on the digital economy.
Towards Supply Chain 4.0
Simulation and Virtual Reality: Simulation is the imitation of the operation of a real-world system or process on a computer platform. With virtual reality and simulation, physical factory systems will be monitored through web-based systems and smart technology applications will proliferate (History of Virtual Reality 2017).
Literature Reviews of Supply Chain 0 based on IoT
The speed of the forklift used in transporting products to the warehouse can be controlled with sensors and the risk of accidents can be minimized. In this way, most of the uncertainties in reverse logistics activities will be eliminated and the cost of logistics will be minimized (Gu and Liu 2013).
Bibliometric Mapping and Clustering Analysis
Overlay visualization of cited authors is shown in Figure 15, the size of the nodes represents the number of citations and the proximity of the nodes is related to the partnership of the authors. The co-citation analysis reveals the overall strength of the co-citation links with other sources.
Conclusion and Future Studies
Using IoT technologies for a collaborative supply chain: A pallet and container tracking application. An optimization approach to increase revenues of the perishable product supply chain with the Internet of Things.
Literature Reviews
IoT has positively impacted supply chain management, and this revolutionary technology makes it possible to control the external and internal environment of the supply chain. With IoT, a smart product produced by a factory can be easily monitored during each stage of the supply chain process, such as production, distribution, storage and consumption.
Problem Definition and Assumptions
Rst,l : The amount of product used at level l is purchased from the sales and collection center. The dismantled products are determined at the sales and collection centers and they are brought to the decomposition centers.
A Computation Experiment 1 General Information
Model Result
Conclusion and Future Studies
Bi-objective integration of sustainable order allocation and sustainable strategic design of the supply chain network with stochastic demand using a new robust hybrid multi-objective metaheuristic. How closed-loop PLM improves knowledge management across the full product lifecycle and enables the factory of the future. A multi-criteria decision-making model for an advanced to-order repair and disassembly system.
C HAPTER 6
Classification of Literature Review
This paper extends the existing literature reviews and provides an updated version by surveying the supplier evaluation and selection literature from 2000 to 2019 focusing on fuzzy logic and fuzzy decision making in SCM. In this paper, only 310 scientific papers written in English (225 journal papers, 18 book chapters and 67 conference papers) published in refereed journals, books and conference proceedings between 2000 and 2019 are examined. The next two sub-sections present in detail single fuzzy approaches and hybrid fuzzy approaches.
Kilincci and Onal (2011) investigated the supplier selection problem of a white good manufacturer in Turkey and applied FAHP to select the best supplier firm for one of its critical parts used in the production of washing machines. Kar (2015) proposed the application of a hybrid approach using fuzzy AHP for the prioritization of evaluation criteria and subsequently the use of fuzzy NN for the selection of the suppliers in the supplier selection problem. 2016) developed an integrated Balanced Scorecard-FAHP model for the supplier selection problem in the automotive industry.
2016) proposed an extended VIKOR based on the cloud model for supplier selection in the nuclear power industry. Zhou and Xu (2017) and Zhou and Xu (2018) proposed an integrated decision-making model for supplier selection. Sharaf (2019) proposed a new flexible multi-attribute cluster decision-making method for supplier selection based on interval-valued fuzzy VIKOR.
Dursun and Karsak (2013) developed a multi-criteria fuzzy group decision-making approach that applied the QFD concept to the supplier selection process. Büyüközkan and Göçer (2017b) presented an interval-valued intuitionistic MOORA fuzzy method for the supplier selection problem in a digital supply chain environment. Hu and Wei (2014) proposed a multi-objective fuzzy integer programming model for the multi-product purchasing supplier selection problem.
2014) presented a comparative analysis of FAHP and FTOPSIS methods in the context of supplier selection decision making. Alegoz and Yapicioglu (2019) developed a hybrid approach based on FTOPSIS, trapezoidal type-2 FAHP and target programming for supplier selection and order allocation problems. Kar (2014) proposed an approach to the supplier selection problem by integrating FAHP and fuzzy goal programming.
- Analysis of the Reviewed Papers 1 Frequency Analysis of DM Approaches
- Observations and Discussions
- Conclusions
Interactive fuzzy multi-criteria decision-making approach for supplier selection and order allocation in a robust supply chain.
C HAPTER 7
- Literature
- Machine Learning
- Introduction to WEKA
- Classification of Supply Chain Data by Using WEKA 1 Material and Methods
Delivery may include delivery time, delivery capability, delivery time, location and transport./The ratio between the number of products delivered on time and the total number of products. Supplier flexibility can be defined as the easy adaptation of the supplier to customer requirements./The flexibility level of potential suppliers. Assurance of the quality of the service offered by the supplier and obligations between the buyer and the supplier, the supplier's communication system with information on the progress data of the order./The level of trust and the communication with potential suppliers.
A multi-objective weighted additive fuzzy model for the supplier selection problem under supply chain price breaks. A supervised machine learning approach for data-driven simulation of flexible supplier selection in digital manufacturing. Integrated AHP soft model and VIKOR soft model for supplier selection in an agile and modular virtual enterprise.
C HAPTER 8
- Long Short Term Memory
- Application
- Implementation
- Performance Measures
- Discussions and Results
- Conclusion
In this chapter, we applied five performance measures to evaluate the results of the proposed approach. While %70 of the data is used in training, the remaining data is used in testing. That's why we only examined one of the most crowded and longest lines to assess the performance of the developed.
C HAPTER 9
- Digitization in Supply Chain Management
- Development of Augmented Reality 1 Augmented Reality (AR)
- AR applications in Supply Chain Management
- Conclusion and Future Directions
Among these areas, order picking accounts for more than 50% of inventory costs (Stoltz et al. 2017). Order picking is one of the logistical operations that AR technology can be used effectively. Google's Glass Enterprise Edition 2 is currently one of the most popular smart glasses on the market.
C HAPTER 10
- Blockchain in Supply Chain and Logistics
- Blockchain and other Emerging Technology Applications
- SWOT Analysis of Blockchain Technology in Supply Chain and Logistics
- Conclusions and Future Directions of Blockchain Technology
Therefore, it is important to understand the application possibilities of blockchain technology in supply chain and logistics. In the food supply chain, many retailers are adopting blockchain technology to track the authenticity of food products. In this sense, blockchain technology will become widespread and widely adopted in the supply chain and logistics industry.
C HAPTER 11
Artificial Intelligence and its Development
In his paper, Selfridge defines pattern recognition as: "the extraction of the significant features of data from a background of irrelevant detail". Today, pattern recognition is one of the main research tasks in the field of AI (Selfridge 1955). Although relatively young, ML is one of the fastest growing technical fields today.
Robotics and Autonomous Systems
The results of the generative component are mainly used for discrimination which is the ultimate goal of hybrid deep networks. The next generation of intelligent, flexible and low-cost robotics technology will be the backbone of the new era of factory automation (Kusiak 2018). Assembly, material handling, welding and painting are some of the basic operations that can be done using these robots.
Industry Applications
Replenishment of the goods from the suppliers to the warehouse or distribution center is the first phase. Finally, the third phase is the delivery of the orders from the distribution centers to customers. Intensive overview of artificial intelligence systems' application in process planning and manufacturing.
C HAPTER 12
- Literature Review
- Problem Definition and Modeling
- Computational Experiments
- Conclusion
Constraints (13) ensure that the sum of the number of disassembled products and component k produced by the 3DP machine cannot be less than the total demand of component k. Because the fixed cost of operating a 3DP machine is much lower, the model tends to increase the number of components produced through the 3DP machine to minimize the objective function value. When the fixed cost of the 3DP machine increases, the number of disassembled products and the objective function value also increase for the current test problem and vice versa.
C HAPTER 13
- Enterprise Resource Planning
- Literature Review of ERP
- Effect of the Industry 4.0 on ERP Systems
- Future Trends of ERP in Industry 0
- Logistics and Industry 4.0
- Warehouse Management and its Functions
- Historical Developments towards Smart Warehouses
- Warehouse Functions
- Warehouse Management and Performance Indicators
- New Technologies used in Warehouses
At the data level, obtaining data from the source and storing it is an important expansion point of the future ERP systems. RFID (Radio Frequency Identification) systems are one of the equipments that can acquire data from the source. The Internet of Things (IoT), where all the parts of the process are connected to each other in the network.
