scholarly journals SIMULATION MODELING OF PRODUCTION LINES: A CASE STUDY OF CEMENT PRODUCTION LINE

2013 ◽  
Vol 41 (3) ◽  
pp. 1045-1053 ◽  
Author(s):  
M. Heshmat ◽  
M. A. El-Sharief ◽  
M. G. El- Sebaie
Keyword(s):  
Production Line ◽  
Simulation Modeling ◽  
Production Lines ◽  
Cement Production

scholarly journals c-Bottlenecks in serial production lines: Identification and application

2001 ◽  
Vol 7 (6) ◽  
pp. 543-578 ◽  
Author(s):  
S.-Y. Chiang ◽  
C.-T. Kuo ◽  
S. M. Meerkov
Keyword(s):  
Cycle Time ◽  
Production Line ◽  
Markovian Model ◽  
Production Lines ◽  
Serial Production ◽  
Automotive Engine ◽  
Machine Reliability ◽  
Bottleneck Identification ◽  
Serial Production Lines

The bottleneck of a production line is a machine that impedes the system performance in the strongest manner. In production lines with the so-called Markovian model of machine reliability, bottlenecks with respect to the downtime, uptime, and the cycle time of the machines can be introduced. The two former have been addressed in recent publications [1] and [2]. The latter is investigated in this paper. Specifically, using a novel aggregation procedure for performance analysis of production lines with Markovian machines having different cycle time, we develop a method for c-bottleneck identification and apply it in a case study to a camshaft production line at an automotive engine plant.

scholarly journals Effect of Preventive Maintenance on the Production Line Machines and Systems Reliability: Case Study

2020 ◽  
pp. 58-65
Author(s):  
A. M. Badiea ◽  
A. A. Adel ◽  
H. A. Aamer
Keyword(s):  
Preventive Maintenance ◽  
Production Line ◽  
Production Lines ◽  
Mean Time Between Failure ◽  
One Year ◽  
Mean Time

The aims of this study are to introduce the appropriate preventive maintenance to the production line machines at the company to increase their reliability and reduction the shutdown, and to obtain more safety. Mean time between failure, mean down time and availability are investigated as the best indicators to generally evaluate all type of maintenance. Pareto diagram and Effect-Cause techniques both have been used for identifying where and what are the problems in the production lines. The big and serious way that the company staff was using was maintenance of run to failure. Many solutions in this paper are introduced to the company to follow the proper preventive maintenance. After one year monitoring to those production lines, their productivity increases by 15.47% and the reliability becomes high.

scholarly journals Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 462
Author(s):  
Bruno Mota ◽  
Luis Gomes ◽  
Pedro Faria ◽  
Carlos Ramos ◽  
Zita Vale ◽  
...  
Keyword(s):  
Demand Response ◽  
Production Line ◽  
Textile Industry ◽  
Complex Problem ◽  
Energy Availability ◽  
Energy Prices ◽  
Production Lines ◽  
Renewable Sources ◽  
Consumption Cost

The scheduling of tasks in a production line is a complex problem that needs to take into account several constraints, such as product deadlines and machine limitations. With innovative focus, the main constraint that will be addressed in this paper, and that usually is not considered, is the energy consumption cost in the production line. For that, an approach based on genetic algorithms is proposed and implemented. The use of local energy generation, especially from renewable sources, and the possibility of having multiple energy providers allow the user to manage its consumption according to energy prices and energy availability. The proposed solution takes into account the energy availability of renewable sources and energy prices to optimize the scheduling of a production line using a genetic algorithm with multiple constraints. The proposed algorithm also enables a production line to participate in demand response events by shifting its production, by using the flexibility of production lines. A case study using real production data that represents a textile industry is presented, where the tasks for six days are scheduled. During the week, a demand response event is launched, and the proposed algorithm shifts the consumption by changing task orders and machine usage.

Study The Effect of Machine Efficiency In Production Lines Balancing

2020 ◽  
Vol 38 (9A) ◽  
pp. 1283-1292
Author(s):  
Rasha J. Marzoog ◽  
Sawsan S. Al-Zubaidyb ◽  
Ahmed A. Alduroobi
Keyword(s):  
Production Line ◽  
Idle Time ◽  
Line Balancing ◽  
Production Flow ◽  
Production Lines ◽  
Work Time ◽  
Efficiency Criterion ◽  
Maximum Production ◽  
On Line

Production Line Balancing (PLB) is the technique of assigning the operations to workstations in such a way that the assignment minimizes the idle time between workstations. PLB aims to equator the workload in each workstation to assure maximum production flow. By adding machine in specific configurations is one treatment which leads to this leveling in workload. This research studies the different efficiencies of the added machine and the effect of these efficiencies on line balancing to select the machine with suitable efficiency. This will be led to reduce the idle time between workstations and increasing production flow. The work time considered as the efficiency criterion for this case study. The study has been implemented on a dumb truck production line and resulted in increasing the line efficiency to 81.7%.

Tackling Means for Balancing the Production Lines

2011 ◽  
Vol 383-390 ◽  
pp. 4620-4628
Author(s):  
Olga Ioana Amariei ◽  
Codruţa Oana Hamat ◽  
Liviu Coman ◽  
Cristian Fănică ◽  
Cristian Rudolf
Keyword(s):  
Production Line ◽  
Idle Time ◽  
Computer Method ◽  
Basic Method ◽  
Assembly Lines ◽  
Production Lines ◽  
Heuristic Techniques ◽  
Human Operators

Balancing a production line means to organize the activity of the human operators, to establish the production flux and designing the line, minimizing the idle time for the machines and the operators, through an optimal charge bestowed upon them. WinQSB software offers three methods of solving this type of problem, namely: heuristic techniques (a basic method is specified and an alternative one from all the available ones), Optimizing Best Bud Search and Computer Method of Sequencing Operations for Assembly Lines, presented all in the present paper.

scholarly journals Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study

2021 ◽  
Vol 11 (8) ◽  
pp. 3487
Author(s):  
Helge Nordal ◽  
Idriss El-Thalji
Keyword(s):  
Simulation Model ◽  
Simulation Modeling ◽  
Study Data ◽  
Opportunistic Maintenance ◽  
Maintenance Strategies ◽  
Modeling Approach ◽  
Intelligent Maintenance ◽  
Diagnosis And Prognosis ◽  
Case Study Data

The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to such models almost impossible. It is also missing enable modeling deterioration based on loading, or considering technical specifications related to detection, diagnosis, and prognosis, which are all decisive for intelligent maintenance purposes. The purpose and scientific contribution of this paper is to present a novel simulation model that enables estimating the lifetime benefits of an industrial asset when an intelligent maintenance management system is utilized as mixed maintenance strategies and the predictive maintenance (PdM) is leveraged into opportunistic intervals. The multi-method simulation modeling approach combining agent-based modeling with system dynamics is applied with a purposefully selected case study to conceptualize and validate the simulation model. Three maintenance strategies (preventive, corrective, and intelligent) and five different scenarios (case study data, manipulated case study data, offshore and onshore reliability data handbook (OREDA) database, physics-based data, and hybrid) are modeled and simulated for a time period of 20 years (175,200 h). Intelligent maintenance is defined as PdM leveraged in opportunistic maintenance intervals. The results clearly demonstrate the possible lifetime benefits of implementing an intelligent maintenance system into the case study as it enhanced the operational availability by 0.268% and reduced corrective maintenance workload by 459 h or 11%. The multi-method simulation model leverages and shows the effect of the physics-based data (deterioration curves), loading profiles, and detection and prediction levels. It is concluded that implementing intelligent maintenance without an effective predictive horizon of the associated PdM and effective frequency of opportunistic maintenance intervals, does not guarantee the gain of its lifetime benefits. Moreover, the case study maintenance data shall be collected in a complete (no missing data) and more accurate manner (use hours instead of date only) and used to continuously upgrade the failure rates and maintenance times.

Design and Validation of a Simulation-Based Modular Planning and Scheduling System of Semiconductor Fabrication Facilities

2011 ◽  
Vol 48-49 ◽  
pp. 378-381
Author(s):  
Li Li ◽  
Fei Qiao
Keyword(s):  
Simulation Modeling ◽  
General Structure ◽  
Structure Model ◽  
Planning And Scheduling ◽  
Scheduling System ◽  
Information Layer ◽  
Simulation Based ◽  
Semiconductor Fabrication ◽  
Control Modules

A simulation-based modular planning and scheduling system developed for semiconductor fabrication facilities (SFFs) is discussed. Firstly, the general structure model (GSM) for SFFs, composed of a configurable definition layer, a physical layer, a process information layer and a planning and scheduling layer, is proposed. Secondly, a data-based dynamic simulation modeling method is given. Thirdly, a simulation-based modular planning and scheduling system (SMPSS) for SFFs, including model modules, release control modules, scheduling modules and rescheduling modules, is designed and developed. Finally, a case study is used to demonstrate the effectiveness of

scholarly journals Study on process of chemical fiber filament automatic doffing system based on simulation platform and machine learning

2021 ◽  
Vol 16 ◽  
pp. 155892502110548
Author(s):  
Hongxin Zhu ◽  
Kun Zou ◽  
Wenlan Bao
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Production Line ◽  
Simulation Platform ◽  
Chemical Fiber ◽  
Production Lines ◽  
The Neural Network ◽  
Spss Software ◽  
The Relationship

In recent years, a large number of automatic equipment has been introduced into the chemical fiber filament doffing production line, but the related research on the fully automatic production line technology is not yet mature. At present, it is difficult to collect data due to test costs and confidentiality. This paper proposes to develop a simulation platform for a chemical fiber filament doffing production line, which enables us to effectively obtain data and quantitatively study the relationship between the number of manual interventions and other process parameters of the production line. Considering that the parameter research is a multi-factor problem, an orthogonal test was designed by using SPSS software and was carried out by using a simulation platform. The multiple linear regression (MLR) and the neural network optimized by genetic algorithm were adopted to fit the relationship between the number of manual interventions and other parameters of the production line. The SPSS software was applied to obtain the standardized coefficients of the multiple linear regression fitting and the neural network mean impact value (MIV) algorithm was applied to obtain the magnitude and direction of the impact of different parameters on the number of manual interventions. The above results provide important reference for the design of similar new production lines and for the improvement of old production lines.

scholarly journals Implementation of Lean Manufacturing in a Cement Industry

2021 ◽  
Vol 11 (3) ◽  
pp. 7069-7074
Author(s):  
M. Masmali
Keyword(s):  
Production Line ◽  
Lean Manufacturing ◽  
Production Control ◽  
Value Added ◽  
Cement Industry ◽  
Shop Floor ◽  
Value Stream Mapping ◽  
Cement Production ◽  
Work In Process ◽  
Production Processes

The lean manufacturing concept is a systematic minimization of waste and non-value activities in production processes introduced by the Toyota production system. In this research, lean manufacturing is implemented in a cement production line. Value Stream Mapping (VSM) is applied to give a clear picture of the value chain in cement production processes and to highlight the non-value-added in the shop floor. To begin, the existing VSM is constructed based on the information and data gathered during visiting and observing the manufacturing process in the firm. As a result, the excess inventory between workstations was identified as a major waste generation, hence, the proposed VSM conducts further improvement and makes action plans to alleviate the unwanted activities. Then, the takt time to ensure smooth material flow and to avoid any occurring delay or bottleneck in the production line was figured out. The supermarket pull-based production control is suggested to be adopted in the future map. Two pull production strategies are selected in this case. The first is applying the Kanban system to control the level of inventory between workstations. The other is the CONWIP approach to control the amount of work in process to the entire production line. The outcome of the proposed models indicates a decrease of the none-value time from 23 days in the current state to about 4 and 2 days in Kanban and CONWIP systems respectively, so the CONWIP was suggested as most efficient. Some suggestions for further research are also mentioned.

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