Improved Decision-Making through a DEMATEL and Fuzzy Cognitive Maps-Based Framework

The decision-making process is highly demanding. There has been an increasing tendency to incorporate human thinking, individual experience about a problem, and pure mathematical approaches. Here, a novel integrated approach is investigated and proposed to develop an advanced hybrid decision-support system based on the decision-making trial and evaluation laboratory (DEMATEL) and fuzzy cognitive maps (FCMs). Indeed, knowledge acquisition and elicitation may present distortions and difficulties finding a consensus and an interpretation. Thus, the proposed combined approach aims to examine in depth the potential to improve FCMs' outcomes by integrating FCM with the DEMATEL approach. The combined methodology achieves at avoiding some of the drawbacks, such as the lack of a standardized FCM theoretical model. Thus, it provides advanced comparative analysis and results in better interpretation of the decision-making process. It is highlighted that the traditional FCM approach does not allow distinguishing the whole number of defined scenarios, in contrast to the hybrid one presented here, which increases the ability of users to make correct decisions. Combining the two approaches provides new capabilities to FCMs in grouping experts' knowledge, while the DEMATEL approach contributes to refining the strength of concepts' connections

Artificial Intelligence to Solve Production Scheduling Problems in Real Industrial Settings: Systematic Literature Review

This literature review examines the increasing use of artificial intelligence (AI) in manufacturing systems, in line with the principles of Industry 4.0 and the growth of smart factories. AI is essential for managing the complexities in modern manufacturing, including machine failures, variable orders, and unpredictable work arrivals. This study, conducted using Scopus and Web of Science databases and bibliometric tools, has two main objectives. First, it identifies trends in AI-based scheduling solutions and the most common AI techniques. Second, it assesses the real impact of AI on production scheduling in real industrial settings. This study shows that particle swarm optimization, neural networks, and reinforcement learning are the most widely used techniques to solve scheduling problems. AI solutions have reduced production costs, increased energy efficiency, and improved scheduling in practical applications. AI is increasingly critical in addressing the evolving challenges in contemporary manufacturing environments

Designing an Efficient Production System: A Case Study of a Clothing Company

This paper is based on a discrete-event simulation model and reproduces the sewing department of a clothing company involved in the fashion industry. It aims to quantitatively assess the effects of different production configurations on flow time and production In particular, the production phases of men’s jackets are examined. Eight configurations are evaluated, stemming from the combination of two parameters: batch size and number of machines. For each configuration, the flow time, the production capacity and the waiting time are computed. A subsequent Design of Experiment (DoE) analysis has been performed on these configurations, with the aim of identifying significant single and combined effects of the above parameters on the results observed. The goal is to obtain improvements in the production process. The data provided by the simulation is used in order to make a critical analysis of the system production and leads to the formation of proposals for the improvement of the lay-out

Rationale, design and methods of the HEALTHY study physical education intervention component

The HEALTHY primary prevention trial was designed to reduce risk factors for type 2 diabetes in middle school students. Middle schools at seven centers across the United States participated in the 3-year study. Half of them were randomized to receive a multi-component intervention. The intervention integrated nutrition, physical education (PE) and behavior changes with a communications strategy of promotional and educational materials and activities. The PE intervention component was developed over a series of pilot studies to maximize student participation and the time (in minutes) spent in moderate-to-vigorous physical activity (MVPA), while meeting state-mandated PE guidelines. The goal of the PE intervention component was to achieve ≥150 min of MVPA in PE classes every 10 school days with the expectation that it would provide a direct effect on adiposity and insulin resistance, subsequently reducing the risk of type 2 diabetes in youth. The PE intervention component curriculum used standard lesson plans to provide a comprehensive approach to middle school PE. Equipment and PE teacher assistants were provided for each school. An expert in PE at each center trained the PE teachers and assistants, monitored delivery of the intervention and provided ongoing feedback and guidance

ANALYSIS OF INJURY EVENTS BY MEANS OF FUZZY COGNITIVE MAPS

Issues related to health and safety at work, such as accidents at work, are one of the most important areas of action for global social policy. This paper presents a fuzzy cognitive map (FCM) approach to explore the importance of the relevant factors in industrial plants. For this purpose, industrial plants are described in terms of factors that affect injury risk and the causal relationships involved. In this work, the injuries in an Italian refinery have been studied. The company in this account has a system for monitoring and controlling the machinery but has a large number of minor injuries at work. The causes of these injuries have been found in human behaviours. To analyse the injuries, it is necessary to investigate what individual-level concerns are involved in the perception of risk. For this investigation, an FCM permits us to build a schema of the perception of risk. The resulting analysis of all of these schemas has allowed us to define a method that generically permits a determination of the causes for each type of injury. In fact, it has been possible to determine that factors such as poor attention and concentration or fatigue are the main causes of injuries at work. In light of the results obtained, managers can define appropriate control procedures to diminish the occurrences of the injuries

SUPPLY CHAIN MODELLING AND MANAGING, USING TIMED COLORED PETRI NETS: A CASE STUDY

This paper aims at developing a new methodology for designing and managing a supply chain (SC) and, at the same time, for evaluating the performance of every stakeholder involved in a production chain. The methodology proposed has been applied to a footwear supply chain and is based on coloured Petri nets (CPNs). The supply chain analysed in this paper is a complex production system consisting of a network of manufacturers and service suppliers related to logistics systems that provide transportation and storage. The model developed uses coloured, timed Petri nets to represent a supply chain and it is such that resources are the Petri Net (PN) places, the tokens are jobs, orders and/or products, while the colours represent job attributes. These colours are used to encode different data types and values that are attached to tokens. A “coloured token” represents a specific production order or a certain amount of a particular material supplied. Thus, it can be processed in different ways and it can be easily localised within the CPN model. The use of coloured Petri nets allows companies to create a compact representation of states, actions and events of the modelled system. The particular structure of this network allows the designers the easy realisation of a simulator using an “object-oriented”, dedicated programming, which is a useful tool for developing what-if analyses

The impact of business growth in the operation activities: a case study of aircraft ground handling operations

This work aims at developing a Business Process Re-Engineering (BPR) method for analysing and overcoming the impact of business growth in the operation activities. A framework based on Delphi method, IDEF3 methodology, discrete event simulation and Design of Experiment is presented for predicting future scenarios and analysing the consequences. The case study of an Italian airport, has been analysed in order to explain the proposed approach. In particular, the company that manages the airport aims at increasing the air traffic and it is necessary to assess the impact of this choice on ground handling operations. The BPR procedure proposed in this work allowed the company to analyse the As-Is ground handling processes and to design a To-Be scenarios for improving the service efficiency and quality