The technical-business aspects of two mid-sized manufacturing companies implementing a joint simulation model

One of the controversial issues in manufacturing systems is bottleneck. Managers and engineers are trying to find methods to eliminate the bottlenecks and waiting times in the production line. More over the manufacturing companies are striving to sustain their competiveness by decreasing the bottlenecks, total cost and increasing the productivity. The objective of this study is applying the computer simulation to analysis the production line bottlenecks. To achieve this goal a color manufacturing line was selected as a case study and the basic application of arena 13.9 software. Finally the some modifications in the simulation model are proposed to improve the production line as well as to decrease the bottleneck.

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Modeling and Simulating Long-Stroke Valve-Controlled Asymmetrical Cylinder Based on MATLAB/Simulink

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.337.695 ◽

2011 ◽

Vol 337 ◽

pp. 695-700

Author(s):

Yong Feng Li ◽

Zhi Quan Xiao

Keyword(s):

Simulation Model ◽

Flow Rate ◽

Dynamic Performance ◽

State Equations ◽

Matlab Simulink ◽

Joint Simulation ◽

Flow Pressure ◽

Set Up ◽

Long Stroke ◽

Dynamic Performance Analysis

Abstract. Based on the redefined flow rate and flow pressure, the forward and backward state equations of long-stroke valve-controlled asymmetrical cylinder system are set up, in which the general mistakes in building up the flow rate equation are avoided. Then the simulation model in MATLAB/Simulink is established. Adopting the conditional-executive subsystem blocks, joint simulation with different models at two directions is realized by taking into account the continuity problems in positioning reversal. The subsystem of introduced equivalent volume function helps to show the effects of piston working position to valve-controlled cylinder system. Furthermore, with this simulation model, dynamic performance analysis of long-stroke valve-controlled asymmetrical cylinder system including some nonlinear factors becomes convenient.

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Development of a Knee Joint Simulation Model considering the Length Patterns of the MCL

The Proceedings of Mechanical Engineering Congress Japan ◽

10.1299/jsmemecj.2020.j02205 ◽

2020 ◽

Vol 2020 (0) ◽

pp. J02205

Author(s):

Ryo TAKEDA ◽

Shun SHINOHARA ◽

Katsuhiko SASAKI ◽

Shinya HONDA

Keyword(s):

Knee Joint ◽

Simulation Model ◽

Joint Simulation

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Study on the Vibration Active Control of Three-Support Shafting with Smart Spring While Accelerating over the Critical Speed

Applied Sciences ◽

10.3390/app10176100 ◽

2020 ◽

Vol 10 (17) ◽

pp. 6100 ◽

Cited By ~ 1

Author(s):

Miao-Miao Li ◽

Liang-Liang Ma ◽

Chuan-Guo Wu ◽

Ru-Peng Zhu

Keyword(s):

Simulation Model ◽

Vibration Control ◽

Control Strategy ◽

Critical Speed ◽

Vibration Reduction ◽

Great Influence ◽

Control Force ◽

Joint Simulation ◽

Shaft System ◽

Simulation Results

Smart Spring is a kind of active vibration control device based on piezoelectric material, which can effectively suppress the vibration of the shaft system in an over-critical state, and the selection of control strategy has great influence on the vibration reduction effect of the Smart Spring. In this paper, the authors investigate the control of the over-critical vibration of the transmission shaft system with Smart Spring, based on the ADAMS and MATLAB joint simulation method. Firstly, the joint simulation model of three-support shafting with Smart Spring is established, and the over-critical speed simulation analysis of the three-support shafting under the fixed control force of the Smart Spring is carried out. The simulation results show that the maximum vibration reduction rate is 71.6%. The accuracy of the joint simulation model is verified by the experiment of the three-support shafting subcritical vibration control. On this basis, a function control force vibration control strategy with time-varying control force is proposed. By analyzing the axis orbit of the shafting, the optimal fixed control force at different speeds is obtained, the control force function is determined by polynomial fitting, and the shafting critical crossing simulation under the function control force is carried out. The simulation results show that the displacement response of the shafting under the function control force is less than that under the fixed control force in the whole speed range.

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Throughput Analysis on a Multi-state Manufacturing System by Considering Availability

Jurnal Teknik Industri ◽

10.9744/jti.21.2.69-78 ◽

2019 ◽

Vol 21 (2) ◽

pp. 69-78

Author(s):

Nabila Yuraisyah Salsabila ◽

Nurhadi Siswanto ◽

Erwin Widodo ◽

Oryza Akbar Rochmadhan

Keyword(s):

Simulation Model ◽

Production Process ◽

Manufacturing System ◽

System Capacity ◽

Manufacturing Companies ◽

Customer Demand ◽

Manufacturing Networks ◽

Manufacturing Network ◽

A Company ◽

Reliability And Availability

Manufacturing technology becomes more complex as customer demand increases. Most manufacturing companies consist of multi-state manufacturing networks. Therefore, the reliability and availability parameters become an important issue to satisfy customer demand. Unavailability can result in reducing throughput because of decreasing operational production time. To resolve this problem, the buffer inventory can minimize the occurrence of material starving and production blocking during the equipment downtime. This paper will focus on experimenting with buffer inventory levels and the capacity of a multi-state manufacturing network to increase the production throughput on a company that has 70,000 tons per year of capacity. However, due to the unavailability problem, the existing system capacity decreases to 62,175 tons per year. The simulation model is used to improve throughput by modeling the failure interruption and the buffer inventory logics during the production process.

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Development and Implementation of a Three-dimensional Printed Knee Joint Simulation Model Using the Consolidated Framework for Implementation Research: Addressing Local Simulation Needs

Cureus ◽

10.7759/cureus.4364 ◽

2019 ◽

Author(s):

Eugene Krustev ◽

Adam Dubrowski

Keyword(s):

Knee Joint ◽

Simulation Model ◽

Implementation Research ◽

Three Dimensional ◽

Joint Simulation

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A Simulation Model to Improve Productivity in the Pipe Manufacturing Industry

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.55.2.5 ◽

2020 ◽

Vol 55 (2) ◽

Author(s):

Rabia Almamlook ◽

Harith M. Ali ◽

Arz Qwa Alden ◽

Anad Afhaima ◽

Faieza Saad Bodowara ◽

...

Keyword(s):

Simulation Model ◽

Manufacturing Industry ◽

Job Shop ◽

Video Camera ◽

Operational Performance ◽

Scheduling Problems ◽

Manufacturing Companies ◽

Effective Strategies ◽

Increase Productivity ◽

Pipe Manufacturing

Improving productivity in the pipe manufacturing industry is a major challenge that manufacturing companies in contemporary competitive markets face. The purpose of this study was to improve productivity in the pipe manufacturing industry by applying manufacturing principles that employ simulation modeling. An approach to improve productivity which focuses on the process of workstations and workforces was proposed . The proposed approach’s target was to boost the productivity of providing clients’ prerequisites and leaving a few products in the store for other clients. A simulation model based on the data collected from the steel pipe company, Bansal Ispat Tubes Private Limited’s in India, was used to improve its operational performance. The research methodology included a pro-simulation model, suitable distribution and investigating data. The simulation model was created by simulating each work station and assessing all relevant processes depending on the collected data. The real job-shop data was collected from the machinery production line and supervision workers with observations made during the manufacturing process. The techniques used include videotaping of the operation, interviewing liber by a video camera. The best continuous distributions were choose to achieve a suitable statistical model. The outcomes maybe contribute to improving the productivity of the manufacturing industry. Moreover, the results might help solve scheduling problems in modeling and simulating pipe manufacturing, revealing effective strategies to increase productivity in pipe manufacturing. Thus, the findings could encourage healthy competition between businesses and industries.

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Knowledge-Driven Based Performance Analysis of Robotic Manufacturing Cell for Design Improvement

Volume 6: Design, Systems, and Complexity ◽

10.1115/imece2020-23541 ◽

2020 ◽

Author(s):

Tavo Kangru ◽

Kashif Mahmood ◽

Tauno Otto ◽

Madis Moor ◽

Jüri Riives

Keyword(s):

Decision Making ◽

Simulation Model ◽

Product Life Cycle ◽

Virtual Manufacturing ◽

Parametric Models ◽

Smart Manufacturing ◽

Manufacturing Companies ◽

Process Data ◽

Estimation Process ◽

Production Cell

Abstract Manufacturing companies must ensure high productivity and low production cost in rapidly changing market conditions. At the same time products and services are evolving permanently. In order to cope with those circumstances, manufacturers should apply the principles of smart manufacturing together with continuous processes improvement. Smart manufacturing is a concept where production is no longer highly labor-intensive and based only on flexible manufacturing systems, but production as a whole process should be monitored and controlled with sophisticated information technology, integrated on all stages of the product life cycle. Process improvements in Smart Manufacturing are heavily reliance on decisions, which can be achieved by using modeling and simulation of systems with different analyzing tools based on Big Data processing and Artificial Intelligence (AI) technologies. This study was performed to automate an estimation process and improve the accuracy for production cell’s performance evaluation. Although there have been researches performed in the same field, the substantial estimation process outcome and accuracy still need to be elaborated further. In this article a robot integrated production cell simulation framework is developed. A developed system is used to simulate production cell parametric models in the real-life situations. A set of rules and constraints are created and inserted into the simulation model. Data for the constraints were acquired by investigating industries’ best production cells performance parameters. Information was gathered in four main fields: company profile and strategy, cell layout and equipment, manufactured products process data and shortcomings of goal achievements or improvement necessary to perform. From those parametric case model, a 3D virtual manufacturing simulation model is built and simulated for achieving accurate results. The integration of manufacturing data into decision making process through advanced prescriptive analytics models is a one of the future tasks of this study. The integration makes it possible to use “best practice” data and obtained Key Performance Indicators (KPIs) results to find the optimal solutions in real manufacturing conditions. The objective is to find the best solution of robot integrated cell for a certain industry using AI enabled simulation model. It also helps to improve situation assessment and deliberated decision-making mechanism.

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