Simulation Of Production Line Research Articles

Cyber-physical manufacturing systems: An architecture for sensor integration, production line simulation and cloud services

The pillars of Industry 4.0 require the integration of a modern smart factory, data storage in the Cloud, access to the Cloud for data analytics, and information sharing at the software level for simulation and hardware-in-the-loop (HIL) capabilities. The resulting cyber-physical system (CPS) is often termed the cyber-physical manufacturing system, and it has become crucial to cope with this increased system complexity and to attain the desired performances. However, since a great number of old production systems are based on monolithic architectures with limited external communication ports and reduced local computational capabilities, it is difficult to ensure such production lines are compliant with the Industry 4.0 pillars. A wireless sensor network is one solution for the smart connection of a production line to a CPS elaborating data through cloud computing. The scope of this research work lies in developing a modular software architecture based on the open service gateway initiative framework, which is able to seamlessly integrate both hardware and software wireless sensors, send data into the Cloud for further data analysis and enable both HIL and cloud computing capabilities. The CPS architecture was initially tested using HIL tools before it was deployed within a real manufacturing line for data collection and analysis over a period of two months.

Real-time data-driven discrete-event simulation for garment production lines

The garment industry, which is traditionally labour-intensive, is facing significant challenges to reduce production costs in the face of material, labour, and infrastructure maintenance cost increases. To address this challenge, various aspects of smart factory-related technologies are being adopted by the garment industry. In this study, we introduce a production line simulation approach based on real-time power monitoring data in the form of garment production workers’ individual task times. Power consumption data for workers’ sewing machines are collected using ICT-based power monitoring devices, and the data are transmitted to a cloud server through a wireless network and processed by an approximation algorithm to extract accurate task time. Power monitoring data are then used as inputs to a discrete-event simulation model to measure the overall productivity, individual productivity, and other key performance indices critical to the garment production line. The simulation results were 18.8% more accurate than the results obtained by the garment production line using a conventional approach. This study demonstrates the potential of smart factory-related technologies and how they can be implemented in different types of industries, such as the garment production industry.

Design of Simulation Verification Platform for Ship Sub Assembly Digital Production Line Control System

The early verification of the control system of the sub assembly production line plays an important role in the efficiency and quality of the production line. The traditional control system verification is based on the actual production line and the cost is high. This paper proposes a simulation verification platform with data interaction with the control system, which can verify the control system at low cost. It can enable the ship sub assembly laboratory to have the ship sub assembly production line simulation, testing, and development capabilities to meet the research needs of the ship sub assembly production line.

Research on key technology of intelligent production line of aircraft structural parts based on intelligent manufacturing

The rapid development of new generation information technology and artificial intelligence and its integration in the manufacturing field have spurred advanced manufacturing countries to actively explore the development strategy of intelligent manufacturing, in order to realize the interconnection and interoperability of manufacturing processes and life cycle data. And the dynamic optimization of decision-making, ultimately achieving manufacturing automation, flexibility, intelligence, and synergy. Starting from the characteristics of intelligent manufacturing, combined with technical practice and theory, it mainly analyzes the key technologies of intelligent production lines for aircraft structural parts to improve the intelligent manufacturing of aircraft structural parts, from equipment technology, intelligent production technology, intelligent production execution technology, intelligent management technology. In one aspect, the technologies involved in the production line are interpreted, namely, data acquisition technology, intelligent equipment technology, intelligent process design technology, production line modeling and simulation technology, production line maintenance guarantee technology, and intelligent management and control technology.

基于Plant Simulation的SMT生产线仿真技术研究

基于Plant Simulation的SMT生产线仿真技术研究

Simulation and optimization of industrial production lines

Abstract Simulation and optimization techniques are the pillars of for the Virtual Commissioning of modern digital factories. In particular, industrial production lines are complex systems formed by a set of machines that have several cross-dependencies (i. e., the production efficiency of a machine impact deeply performance figures of the others and affects the whole line productivity). The simulation and optimization of production lines is an integrated approach that allows finding efficiently optimized production parameters. This paper presents an example of application of the simulation to the virtual design and optimization of an industrial production line.

Communication Concept of DeConSim: a Decentralized Control Simulator for Production Systems

In recent years, the price pressure and demand for personalised products in manufacturing increased continuously. As a reaction, technologies from the Information and Communication Technology (ICT) sector are applied by the industry, this trend is also known as digitalisation or Industry 4.0. Digitalisation might be effectively supported by simulation of production lines and will become crucial for manufacturing companies who want to benefit from the advances in ICT technologies, thus improving efficiency and competitiveness. Many agent-based simulators exist, nevertheless, most of them were developed for biological and social sciences whose use and specifications differ significantly from industrial applications. The commercial ones are expensive in terms of licensing, support and require specific training. We propose a communication concept for the simulator that we are developing called DeConSim, which aims at decentralized systems and is composed of several modules (representing resources, each with its own task and intelligence) and a core. DeConSim is capable of operating in two different modes: simulation mode and realtime mode. The former is used to achieve pure simulation results as fast as possible. The latter operates in real-time enabling DeConSim, in contrast to other existing simulators, to become the operational core of the control communication infrastructure of a real production line.

Event-driven Modelling Method for Sub-assembly Intelligent Production Line

Focusing on the design of sub-assemble intelligent production line, an event-driven design method for production line was proposed. With the method, the manufacturing activity was defined as event, and then the relationships among events are analysed to define the input-output and execution behaviours digitally in each stage. Furthermore, the event-driven execution mechanism for multi-stage process was built to describe the production line in digital. The digital model of production line was conducted to explore the event behaviours, which will support the research about data-driven production line simulation in future work.

Implementation of parametric design philosophy into industrial production line simulation for c-Si PV modules

Power generation from photovoltaic (PV) cells is a well-established and promising technology that takes full advantage of solar energy, which is a renewable energy source. Although numerous methods of PV recycling have been proposed worldwide, Greece has not taken any serious corresponding action until now. Moreover, estimations expect that the overall quantity of c-Si PV waste in Europe will reach 3,500,000 tons until 2040 (Bio Intelligence Service, 2011) while in Greece, until 2038 the amount will be in the range of 264,000 tons (Katsigiannis et al., 2014). As a result, it is essential to propose a unified management of PV end-of-life (EOL) process, in order to achieve a successful recovery of materials such as silicon, aluminium, silver and glass. The scope of this paper is the simulation of an integrated c-Si PV recycling process with the use of CATIA software. The design of this recycling process is parametric, in order to allow the location and sizing configuration of each machine and installation type that can be used.

Implementation of parametric design philosophy into industrial production line simulation for c-Si PV modules

Power generation from photovoltaic (PV) cells is a well-established and promising technology that takes full advantage of solar energy, which is a renewable energy source. Although numerous methods of PV recycling have been proposed worldwide, Greece has not taken any serious corresponding action until now. Moreover, estimations expect that the overall quantity of c-Si PV waste in Europe will reach 3,500,000 tons until 2040 (Bio Intelligence Service, 2011) while in Greece, until 2038 the amount will be in the range of 264,000 tons (Katsigiannis et al., 2014). As a result, it is essential to propose a unified management of PV end-of-life (EOL) process, in order to achieve a successful recovery of materials such as silicon, aluminium, silver and glass. The scope of this paper is the simulation of an integrated c-Si PV recycling process with the use of CATIA software. The design of this recycling process is parametric, in order to allow the location and sizing configuration of each machine and installation type that can be used.

Simulation of Production Lines in the Education of Engineers: How to Choose the Right Software?

Abstract The article discusses the problems of modeling and simulation in the design of production lines, mainly from an educator's perspective. Nowadays, there is a wide range of computer programs that can be used to design production lines and to simulate various aspects of their operation. However, the programs being available vary considerably as to their functionality, the approach to production system design, and the visualization tools. Therefore we demonstrate and evaluate in this paper four simulation programs, focusing on the easiness of system design, area of the possible applications in education of engineers, and the limitations imposed by versions dedicated for students. We evaluate three of programs for digital factory simulation on a common, simple assembly task, then demonstrate that these programs may be also used for more specialized simulations in various areas of production, and compare with a specialized program for simulation of robotised production lines and work cells.

A Simulation and Optimization Study of Assemble Production Line

As to the BSP model assembly line balancing problem, an integration to random distribution about the field data in statistical software of SPSS, is made in the paper with software of eM-Plant, a model and simulate to the production line is built to discover the bottleneck of the production line and the unbalance problem of line fast and accurately. The optimization design and simulation analysis and evaluation can be achieved to optimization goal and shorten the optimization time.

Virtual simulation of production line for ergonomics evaluation

To avoid ergonomic problems in the early planning stages of a production line and achieve more satisfactory planning and design, ergonomic simulation is particularly important in digital production line planning. An ergonomics analysis method is presented by using two theories: Ovako working posture analysis system (OWAS) and Burandt-Schultetus hand-arm force analysis (BSHA). The processes of ergonomics analysis and simulation are discussed based on a platform of process simulation and process designer. As an example, the paper shows how ergonomics problems are considered in production line planning to make a better choice between different production line planning schemes.

A Rapid Simulation and Optimization Study of Production Line

Based on intermittent production line balance problem, Minitab statistical tool is used for data random distribution fitting in this paper and the car body production line model of one company is established and simulated under Flexsim environment, which benefits the line imbalance problem to be found quickly and accurately. Designing optimal program based on project management network analysis and making simulation and evaluation, the productivity is improved effectively and the time to balance and optimize production line is shortened greatly.

Artificial bee colony algorithm for CONWIP production control system in a multi-product multi-machine manufacturing environment

In this paper, a multi-product multi-machine serial production line operated under a constant-work-in-process protocol is considered. A mathematical model for the system is first presented, and then an artificial bee colony optimization algorithm is applied to simultaneously find the optimal work-in-process inventory level as well as job sequence order in order to minimize the overall makespan time. Unlike many existing approaches, which are based on deterministic search algorithms such as nonlinear programming and mixed integer programming, the proposed method does not use a linearized or simplified model of the system. A production line simulator implemented on MATLAB is, instead, employed to model the highly nonlinear dynamics of the production line and is used to evaluate the candidate solutions. The efficiency of the proposed approach, even for systems of large sizes, is validated via numerical simulations.

Study On Simulation Of The Main Shaft Production Line

Since modern production system is a highly complicated discrete manufacturing system, it is very difficult to design the production line by traditional means. However, through building model of production system in virtual environment, analyzing and evaluating production system performance based on system simulating technology, the production system’s parameter and configuration can be optimized ahead of production plan to optimize production process and improve production efficiency. In this paper, the main shaft production line simulation model is constructed based on the object oriented discrete system software eM-Plant. The production line throughput, utilization and bottleneck operations are analyzed. Based on this, it can support the configuration of production line optimized. The example verifies that the modeling and simulation technology could be successfully used in manufacturing industry.

Simulation and Optimization of the Camshaft Production Line Based on Petri Net

With the development of scientific and technology, the automotive industries competition is becoming more and tougher. The camshaft production system is an important part of the engine manufacturing. The production line productivity and characteristic are affected by many practical factors of the workshop. It’s a complex discrete manufacturing system somehow. In this paper, the production line model is presented based on Petri net. Then the mapping relationship is established between the Petri net model and the eM-Plant discrete system model. The discrete simulation model of production line is constructed by using eM-plant software. Based on the simulation, the reasonable simulation experimental are carried out with the determined simulation boundary and objectives under the different input conditions such as orders, the working stations' processing time, the working stations’ fault distribution, and the production line layout. The simulation experimental results are discussed on condition that the shifts, equipment operation condition, production line capacity and WIP in detail. These results could provide the theory basis for decision-making of the production plan of the automotive industries.

A new method for the placement of buffers in serial production lines

The placement of buffers in a production line is an old and well-studied problem in industrial engineering/operations research that is still relevant today. Decisions regarding the amount and placement of buffers in a production line occur repeatedly in system design. In this paper we document a new buffer placement method for serial production lines that operate under a variety of assumptions. The method uses information generated in a production line simulation, whose conceptual representation of job flow and workstation interaction can be described with a network, to place buffers in order to maximise throughput. This buffer placement method is very efficient and can be implemented in a spreadsheet. We demonstrate the effectiveness of the method by comparing our results against those produced by a genetic algorithm for buffer placement. Experiments are conducted on a variety of test cases. This new buffer placement optimisation method will permit designers to quickly and effectively evaluate many design alternatives and thus improve final production system performance.

Simulation of production lines - the importance of breakdown statistics and the effect of machine position

This paper demonstrates the importance of choosing the correct values and statistical distributions for breakdown frequency and duration when simulating production line productivity. Statistical distributions with a wide range tend to reduce the productivity of the line but this trend can be disrupted by poor choice of mean values for the variables in question. Also, it is demonstrated that the productivity of a production line can be improved simply by re-arranging the order of unreliable machines in the line. If the line consists of similar or exchangeable machines, productivity can improved if the most unreliable machines are placed towards the end of the line. The paper also demonstrates the risks of reduction of the standard deviation to obtain a more deterministic model. (Received in December 2007, accepted in July 2008. This paper was with the authors 2 months for 1 revision.)

Stochastic modelling and simulation of production lines: a computer-based approach towards model validation

This study employs a simulation-based design methodology to investigate the performance of two models of manufacturing systems. In the first model, the dynamic behaviour of a single parallel-machine stage with unreliable work stations is modelled as a Markov process. A similar analytical method for evaluating the performance of a buffered production line is presented in the second model. A simple approach towards coding and simulating the models is presented, and numerical examples based on these simulation models indicate that the approach is viable.