Perspectives and relationships in Supply Chain Simulation: A systematic literature review

Systems simulation - the art and science

The possibilities of applying Operations Research (O.R.) techniques in the design of real-world systems are vast. The optimization and design of the supply chain network (SCN) is one of the relevant topics that has directed the attention of many scholars. Sound decisions in this regard, including the proper selection of the facility’s location, transportation modes and routes and inventory management policies, can noticeably improve the systems performance. Over 380 articles published between 2005 and 2016 in the ISI/Web of Science database have applied advanced O.R. techniques in SCN optimization studies. This paper offers a systematic review of these published contributions by focusing on two categories of O.R. approaches most recently applied for the design of SC systems: integrated mathematical modeling and simulation-optimization (S-O) frameworks. A taxonomy analysis of the mentioned approaches is presented based on the supply chain elements. A bibliometric analysis is also conducted to provide technical insights into the possible gaps in the field. Moreover, the relevant studies on SC sustainability are highlighted. The research results are supportive of the S-O frameworks as either an alternative approach or an effective solution method for the integrated problems. The research outcomes can provide researchers in the field with useful details of the integrated problems and S-O frameworks as the most recent O.R. methodologies in the field of SC optimization.

https://www.mdpi.com/2071-1050/8/10/1033/pdf

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Evolution of carbon capture and storage research: Trends of international collaborations and knowledge maps

Now a day's manufacturing has become more intelligent and data-driven. A smart production unit can be thought of as a powerful connected industrial system with materials, parts, equipment, tools, inventory, and logistics that can transmit data and communicate with one another in the age of the Industrial Internet of Things (IIoT). This IIoT refers to linked devices, sensors, and other equipment that may be networked in the industrial environment to provide remote access, effective monitoring, better data collecting, analysis, & exchange etc. In Industry 4.0, IIoT is fundamental to transforming cyber-physical systems and production processes through big data and analytics. This paper provides an overview of the IIoT and the technologies that underpin it. The primary benefits and features of IIoT in manufacturing are discussed in detail. Smart Transformations made into the manufacturing field through IIoT Culture are discussed diagrammatically. Finally, twenty-nine significant applications of IIoT in the field of manufacturing are identified and discussed. IIoT can monitor the transport, supply of the goods, consult details on things in warehouses, and check the conditions related to product storage and delivery and allow all dispersed and outsourced operations to be monitored. Therefore, the industry is being revolutionised by IIoT, altering the way industrial enterprises function daily to improve efficiency and performance levels.

Upgrading the manufacturing sector via applications of Industrial Internet of Things (IIoT)

Industry 4.0 is having a great impact in all smart efforts. This is not a single product but is composed of several technologies, one of them being Industrial Internet of Things (IIoT). Currently, there are very varied implementation options offered by several companies, and this imposes a new challenge to companies that want to implement IIoT in their processes. This challenge suggests using multi-criteria analysis to make a repeatable and justified decision, requiring a set of alternatives and criteria. This paper proposes a new methodology and comprehensive criteria to help organizations to take an educated decision by applying multi-criteria analysis. Here, we suggest a new original use of PROMETHEE-II with a full example from weight calculation up to IIoT platform selection, showing this methodology as an effective study for other organizations interested in selecting an IIoT platform. The criteria proposed stands out from previous work by including not only technical aspects, but economic and social criteria, providing a full view of the problem analyzed. A case of study was used to prove this proposed methodology and finds the minimum subset to reach the best possible ranking.

https://www.mdpi.com/2073-8994/12/3/368/pdf

Implementing a Novel Use of Multicriteria Decision Analysis to Select IIoT Platforms for Smart Manufacturing

Analysis of scientific collaboration patterns in the co-authorship network of Simulation–Optimization of supply chains

Industry 4.0 is having a great impact in all industries. This is not a unique product, but is composed of several technologies. IoT is a key intelligent factor that allows factories to act intelligently. By adding sensors and actuators to the objects, the object becomes intelligent because it can interact with people, other objects, generate data, generate transactions and react to the environment data. Currently there are very varied implementation options offered by several companies, and this imposes a new challenge to companies that want to implement IoT in their processes. The decision processes that companies must follow should not be free will or by hunches, since this contradicts a methodology and would make the decision process unrepeatable and unjustifiable. Decisions must be supported by methods that consider pros and cons of plural points of view that affect the decision process. With a wide range of IoT platforms, which are not directly comparable to each other, it seems that Multi-Criteria Decision Analysis (MCDA) can be useful to help companies make a decision on what platform to implement, depending on the circumstances prevailing in each company at the time to make the choice. This article shows the complexity of selecting an IoT platform and provides the key decision criteria that must be taken into account when evaluating IoT Platforms alternatives.

/pdf/selection-of-iot-platform-with-multi-criteria-analysis-4mi0t9uiat.pdf

Selection of IoT Platform with Multi-Criteria Analysis: Defining Criteria and Experts to Interview

http://www.scielo.org.mx/pdf/jart/v11n6/v11n6a13.pdf

Optimizing the Cellular Network Planning Process for In-Building Coverage using Simulation

http://www.scielo.org.mx/pdf/jart/v3n2/v3n2a6.pdf

Mayra Elizondo-Cortés

Papers

Implementing a Novel Use of Multicriteria Decision Analysis to Select IIoT Platforms for Smart Manufacturing

Analysis of scientific collaboration patterns in the co-authorship network of Simulation–Optimization of supply chains

Selection of IoT Platform with Multi-Criteria Analysis: Defining Criteria and Experts to Interview

Optimizing the Cellular Network Planning Process for In-Building Coverage using Simulation

Strategy of solution for the inventory routing problem based on separable cross decomposition