Agent-Based Control System as a Tool towards Industry 4.0: Directed Communication Graph Approach

Agent-based control systems composed of simple locally interacting controller agents with demonstrated complex group behaviour. There have been relatively few implementations of agent-based control systems, mainly because of the difficulty of determining whether simple controller agent strategies will lead to desirable collective behaviour in a large system. The aim of this chapter is to design an agent-based control system for sets of ‘clustered’ controller agents through proposed directed communication graph approach as potent tool for the Industry 4.0. To reach global coordination with focus on real world applications, we use cluster algorithm technique in a set of rules for assigning decision tasks to agents. The outcomes include behavioural pattern, trend of agents and multi-agents usage in rail manufacturing enterprise resource planning and supply chain management. The results of this study showed that the combination of multi-agent system has ability to interact effectively and make informed decision on the type of maintenance actions, resource planning, train arrival times, etc

A case study of product-service integration for train braking systems

A product service system requires coordinated approach from multiple stakeholder groups. Industry, government, and civil society must work together to create and promote the deployment and smooth operation of these systems for a more sustainable economy. The train braking system problem areas such as failure detection, big data collection and sensor-based degradation monitoring have created opportunities for researchers to create jobs in the service sector. The paper aims to design product-service integration train braking system as a big data component with combination of dataset, volume, speed, and data diversity. The big data potentials and analysis using “V” model for train brakes integration and ishikawa diagram for the electro-pneumatic brake system that is applicable to the railcar brakes manufacturing industries fuse railcar’s sensory components innovation to market. This is where advanced analysis to examine the available data and organize it using advanced visualization techniques

A control system for a reconfigurable bending press machine (RBPM)

M. Tech. Industrial EngineeringIn industrial manufacturing systems, one often encounters situations in which motion in two, three or more hydraulic cylinders actuators need to be synchronized. The need for the design of a reconfigurable bending press machine (RBPM) control system prompted the research in the development of an automatic and synchronized system, suitable for the press tool operations, versatile in raising and thrusting of multiple- cylinders with odd numbers. The aim of this research is to design and develop a controller that will control all the modules of a reconfigurable bending press machine for bending box-type sheet metal components

Control System for Electro-hydraulic Synchronization on RBPT

AbstractIn industrial manufacturing systems, situations are often encounters in which motion with two, three or more hydraulic cylinder actuators need to be synchronized. The need for the design of a reconfigurable bending press tool (RBPT) control system prompted the research in the development of an automatic and synchronized system, suitable for press tool operations. The system had to de designed to be versatile in raising and thrusting of multi- cylinders with odd numbers. This paper describes the concept of the design of the control system that will allow the controlling of pressure, flow and synchronous cylinder movements, accompanied by position readings measured by position sensors. The system will work simultaneously; with a maximum assembled of units working together, typically in a number that fits the operation's needs. The aim of the proposed controller is to develop a position control system that incorporates features of a modular controller interfacing with position sensors and detecting the position of the hydraulic cylinder rod through commercially-of-the-shelf (COTS) components

Productivity Improvement Using Simulated Value Stream Mapping: A Case Study of the Truck Manufacturing Industry

The accumulation of process waste in the production line causes fluctuations, bottlenecks, and increased inventory in workstations disrupting process flow. In this paper, the optimal process flow that will improve productivity using simulated value stream mapping (SVSM) for decision-making to provide consistency, minimise errors and non-value adding times in the implementation phase of VSM in the truck manufacturing industry. The proposed methodology applied a discrete event simulation for production process operations improvement to eliminate non-value adding times and provide good quality products at the lowest cost and highest efficiency. The results are the analysis of the current state of the production system in a South African truck manufacturing industry as a potential solution for the production system’s future state. The identified non-value adding times in the six most critical workstations were eliminated by SVSM resulting in a productivity improvement of 4%, most importantly bringing the productivity to 95% and total cycle time improvement to 451 for small units and 466 for large units. The results proposed combined VSM and simulation techniques based on empirical data from the observation during time measurement. The Yamazumi confirms the issues observed and the NVA recorded by showing how close the process cycle times are to the TAKT time, which enhance the LEAN application by DES to increase productivity and performance improvement to remain competitive in the global economy

Energy–Carbon Emissions Nexus Causal Model towards Low-Carbon Products in Future Transport-Manufacturing Industries

Climate change is progressing faster than previously envisioned. Efforts to mitigate the challenges of greenhouse gas emissions by countries through the establishment of the Intergovernmental Panel on Climate Change has resulted in continuous environmental improvements in the energy efficiency and carbon emission signatures of products. In this paper, an energy–carbon emissions nexus causal model was applied using the Leontief Input–Output mathematical model for low-carbon products in future transport-manufacturing industries., The relationship between energy savings, energy efficiency, and the carbon intensity of products for the carbon emissions signature of the future transport manufacturing in South Africa was established. The interrelationship between the variables resulted in a 29% improvement in the total energy intensity of the vehicle body part products, 7.22% in the cumulative energy savings, and 16.25% in the energy efficiency. The scope that has been examined in this paper will be interesting to agencies of government, researchers, policymakers, business owners, and practicing engineers in future transport manufacturing and could serve as a fundamental guideline for future studies in these areas

Energy–Carbon Emissions Nexus Causal Model towards Low-Carbon Products in Future Transport-Manufacturing Industries

Climate change is progressing faster than previously envisioned. Efforts to mitigate the challenges of greenhouse gas emissions by countries through the establishment of the Intergovernmental Panel on Climate Change has resulted in continuous environmental improvements in the energy efficiency and carbon emission signatures of products. In this paper, an energy–carbon emissions nexus causal model was applied using the Leontief Input–Output mathematical model for low-carbon products in future transport-manufacturing industries., The relationship between energy savings, energy efficiency, and the carbon intensity of products for the carbon emissions signature of the future transport manufacturing in South Africa was established. The interrelationship between the variables resulted in a 29% improvement in the total energy intensity of the vehicle body part products, 7.22% in the cumulative energy savings, and 16.25% in the energy efficiency. The scope that has been examined in this paper will be interesting to agencies of government, researchers, policymakers, business owners, and practicing engineers in future transport manufacturing and could serve as a fundamental guideline for future studies in these areas

Energy and Carbon Emission Efficiency Prediction: Applications in Future Transport Manufacturing

The long-term impact of high-energy consumption in the manufacturing sector results in adverse environmental effects. Energy consumption and carbon emission prediction in the production environment is an essential requirement to mitigate climate change. The aim of this paper is to evaluate, model, construct, and validate the electricity generated data errors of an automotive component manufacturing company in South Africa for prediction of future transport manufacturing energy consumption and carbon emissions. The energy consumption and carbon emission data of an automotive component manufacturing company were explored for decision making, using data from 2016 to 2018 for prediction of future transport manufacturing energy consumption. The result is an ARIMA model with regression-correlated error fittings in the generalized least squares estimation of future forecast values for five years. The result is validated with RSS, showing an improvement of 89.61% in AR and 99.1% in MA when combined and an RMSE value of 449.8932 at a confidence level of 95%. This paper proposes a model for efficient prediction of energy consumption and carbon emissions for better decision making and utilize appropriate precautions to improve eco-friendly operation