scholarly journals Data-Driven Manufacturing Simulation: Towards a CPS-Based Approach

2020 ◽  
Author(s):  
Yongkuk Jeong ◽  
Amita Singh ◽  
Masoud Zafarzadeh ◽  
Magnus Wiktorsson ◽  
Jannicke Baalsrud Hauge
Keyword(s):  
Industry 4.0 ◽  
Swot Analysis ◽  
Production Systems ◽  
Traditional Approach ◽  
Data Gathering ◽  
Decision Support Tool ◽  
Future Application ◽  
Support Tool ◽  
Manufacturing Simulation ◽  
Monitoring And Forecasting

Manufacturing simulation has been used as a decision support tool to solve various problems in production systems. However, with the advent of Industry 4.0 and CPS, manufacturing simulation becomes not only a tool for supporting decision-making but also essential for operation, monitoring, and forecasting the production system. In this paper, a traditional approach and a CPS-based approach in manufacturing simulation are compared. In the CPS-based approach, the key processes are divided into 1) data gathering, 2) modeling and simulation, and 3) simulation results analytics and feedback. In addition, a SWOT analysis is conducted to discuss the future application of the manufacturing simulation.

scholarly journals Development of a transboundary model of livestock disease in Europe

2021 ◽  
Author(s):  
Richard Bradhurst ◽  
Graeme Garner ◽  
Márk Hóvári ◽  
Maria de la Puente ◽  
Koen Mintiens ◽  
...  
Keyword(s):  
Production Systems ◽  
National Level ◽  
Decision Support Tool ◽  
Animal Disease ◽  
Control Policies ◽  
Support Tool ◽  
Outbreak Management ◽  
Continental Scale ◽  
Livestock Disease ◽  
Modelling Framework

SummaryEpidemiological models of notifiable livestock disease are typically framed at a national level and targeted for specific diseases. There are inherent difficulties in extending models beyond national borders as details of the livestock population, production systems and marketing systems of neighbouring countries are not always readily available. It can also be a challenge to capture heterogeneities in production systems, control policies, and response resourcing across multiple countries, in a single transboundary model.In this paper we describe EuFMDiS, a continental-scale modelling framework for transboundary animal disease, specifically designed to support emergency animal disease planning in Europe. EuFMDiS simulates the spread of livestock disease within and between countries and allows control policies to be enacted and resourced on per-country basis. It provides a sophisticated decision support tool that can be used to look at the risk of disease introduction, establishment and spread; control approaches in terms of effectiveness and costs; resource management; and post-outbreak management issues.

Using Spreadsheets as a Decision Support Tool

2003 ◽  
pp. 57-71 ◽  
Author(s):  
Stephen Burgess ◽  
Don Schauder
Keyword(s):  
Decision Making ◽  
Small Businesses ◽  
Web Site ◽  
Swot Analysis ◽  
Decision Support Tool ◽  
Support Tool ◽  
Decision Making Processes ◽  
Set Up ◽  
Support Decision Making ◽  
The Web

This chapter discusses a model that has been set up to assist small businesses in the decision-making processes associated with setting up a Web site by which they can interact with their customers. Specifically, the chapter addresses the use of a spreadsheet to support decision-making processes in relation to the level of capital needed to devote to the Web site and who should be used to develop it. The chapter describes the process followed, from the initial SWOT analysis used to collect information about the business to the decision-making process modelled in the spreadsheet.

scholarly journals Multilayer Network-Based Production Flow Analysis

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Tamás Ruppert ◽  
Gergely Honti ◽  
János Abonyi
Keyword(s):  
Production Systems ◽  
Flow Analysis ◽  
Decision Support Tool ◽  
Exploratory Analysis ◽  
Benchmark Problem ◽  
Production Flow ◽  
Multilayer Network ◽  
Support Tool ◽  
Production Technologies ◽  
The Relationship

A multilayer network model for the exploratory analysis of production technologies is proposed. To represent the relationship between products, parts, machines, resources, operators, and skills, standardized production and product-relevant data are transformed into a set of bi- and multipartite networks. This representation is beneficial in production flow analysis (PFA) that is used to identify improvement opportunities by grouping similar groups of products, components, and machines. It is demonstrated that the goal-oriented mapping and modularity-based clustering of multilayer networks can serve as a readily applicable and interpretable decision support tool for PFA, and the analysis of the degrees and correlations of a node can identify critically important skills and resources. The applicability of the proposed methodology is demonstrated by a well-documented benchmark problem of a wire-harness production process. The results confirm that the proposed multilayer network can support the standardized integration of production-relevant data and exploratory analysis of strongly interconnected production systems.

An approach and decision support tool for forming Industry 4.0 supply chain collaborations

2021 ◽  
Vol 125 ◽  
pp. 103391
Author(s):  
Sonia Cisneros-Cabrera ◽  
Grigory Pishchulov ◽  
Pedro Sampaio ◽  
Nikolay Mehandjiev ◽  
Zixu Liu ◽  
...  
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Industry 4.0 ◽  
Decision Support Tool ◽  
Support Tool

scholarly journals Carbon Footprint-Energy Detection for Desalination Small Plant Adaptation Response

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7135
Author(s):  
Latifah Abdul Ghani ◽  
Nora’aini Ali ◽  
Ilyanni Syazira Nazaran ◽  
Marlia M. Hanafiah ◽  
Norhafiza Ilyana Yatim
Keyword(s):  
Carbon Footprint ◽  
Environmental Sustainability ◽  
Production Systems ◽  
Processing System ◽  
Decision Support Tool ◽  
Future Research ◽  
Model Framework ◽  
Support Tool ◽  
Desalination Plant ◽  
Carbon Footprint Assessment

The Life Cycle Assessment (LCA) system, which can be used as a decision support tool for managing environmental sustainability, includes carbon footprint assessment as one of the available methodologies. In this study, a carbon footprint assessment was used to investigate seawater production systems of a desalination plant in Senok, Kelantan, Malaysia. Three stages of the desalination plant processing system were investigated and the inventory database was developed using the relevant model framework. Subsequently, measurements and interpretations were performed on several key indicators such as greenhouse gases, energy efficiency, acidic gases, smog, and toxic gases. Overall, the results of the study indicate that the Reverse Osmosis (RO) technology that is used in the desalination plant in the study area is one of the best options to meet the demands of the environmental sustainability agenda (SDGs). This is due to the lower carbon dioxide (CO2) emission, of about 3.5 × 10−2 kg of CO2 eq per m3/year, that was recorded for the entire operation of the system. However, several factors that influence important errors in carbon footprint decisions, such as the lack of EIA reporting data and the literature on carbon footprint in the Malaysian scenario, in addition to direct and indirect carbon input calculations, need to be identified in more detail in future research.

A Decision Support Tool for Classification of Turkish SMEs’ Industry 4.0 Score Levels

2020 ◽  
pp. 264-276
Author(s):  
Uğurcan Dündar ◽  
Fadime Üney-Yüksektepe ◽  
Zeynep Gergin ◽  
Oğuz Emir ◽  
Güneş M. Gençyılmaz ◽  
...  
Keyword(s):  
Decision Support ◽  
Industry 4.0 ◽  
Decision Support Tool ◽  
Support Tool

scholarly journals Industry 4.0: smart test bench for shipbuilding industry

2020 ◽  
Vol 14 (4) ◽  
pp. 1525-1533
Author(s):  
Antonio Giallanza ◽  
Giuseppe Aiello ◽  
Giuseppe Marannano ◽  
Vincenzo Nigrelli
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
High Speed ◽  
Test Bench ◽  
Production Systems ◽  
Interactive Approach ◽  
Propulsion Systems ◽  
Shipbuilding Industry ◽  
Support Tool

AbstractIndustry 4.0 promises to increase the efficiency of production plants and the quality of the final product. Consequently, companies that implement advanced solutions in production systems will have a competitive advantage in the future. The principles of Industry 4.0 can also be applied to shipyards to transform them into “smart shipyards” (Shipyard 4.0). The aim of this research is to implement an interactive approach by Internet of Things on a closed power-loop test bench equipped with sophisticated sensors that is specifically designed to test high-power thrusters before they are installed on high-speed crafts, which are used in passenger transport. The preliminary results of the proposed Internet of Things-platform demonstrates the efficacy of the decision-making support tool in improving the design of propulsion systems and increasing their efficiency compared to traditional systems.

scholarly journals Application of a model to assess aflatoxin risk in peanuts

2010 ◽  
Vol 148 (3) ◽  
pp. 341-351 ◽  
Author(s):  
Y. S. CHAUHAN ◽  
G. C. WRIGHT ◽  
R. C. N. RACHAPUTI ◽  
D. HOLZWORTH ◽  
A. BROOME ◽  
...  
Keyword(s):  
Large Scale ◽  
Production Systems ◽  
Risk Index ◽  
Temperature Response ◽  
Decision Support Tool ◽  
Fold Increase ◽  
Climatic Conditions ◽  
Aflatoxin Contamination ◽  
Climatic Data ◽  
Support Tool

SUMMARYWhen exposed to hot (22–35°C) and dry climatic conditions in the field during the final 4–6 weeks of pod filling, peanuts (Arachis hypogaeaL.) can accumulate highly carcinogenic and immuno-suppressing aflatoxins. Forecasting of the risk posed by these conditions can assist in minimizing pre-harvest contamination. A model was therefore developed as part of the Agricultural Production Systems Simulator (APSIM) peanut module, which calculated an aflatoxin risk index (ARI) using four temperature response functions when fractional available soil water was <0·20 and the crop was in the last 0·40 of the pod-filling phase. ARI explained 0·95 (P⩽0·05) of the variation in aflatoxin contamination, which varied from 0 toc. 800 μg/kg in 17 large-scale sowings in tropical and four sowings in sub-tropical environments carried out in Australia between 13 November and 16 December 2007. ARI also explained 0·96 (P⩽0·01) of the variation in the proportion of aflatoxin-contaminated loads (>15 μg/kg) of peanuts in the Kingaroy region of Australia during the period between the 1998/99 and 2007/08 seasons. Simulation of ARI using historical climatic data from 1890 to 2007 indicated a three-fold increase in its value since 1980 compared to the entire previous period. The increase was associated with increases in ambient temperature and decreases in rainfall. To facilitate routine monitoring of aflatoxin risk by growers in near real time, a web interface of the model was also developed. The ARI predicted using this interface for eight growers correlated significantly with the level of contamination in crops (r=0·95,P⩽0·01). These results suggest that ARI simulated by the model is a reliable indicator of aflatoxin contamination that can be used in aflatoxin research as well as a decision-support tool to monitor pre-harvest aflatoxin risk in peanuts.

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