scholarly journals IMPROVABILITY OF THE FABRICATION LINE IN A SHIPYARD

Brodogradnja ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 13-28
Author(s):  
Neven Hadžić ◽  
◽  
Viktor Ložar ◽  
Tihomir Opetuk ◽  
Hrvoje Cajner
Keyword(s):  
Continuous Improvement ◽  
Production System ◽  
Manufacturing System ◽  
Discrete Event ◽  
Event Simulation ◽  
Work In Process ◽  
Bottleneck Identification ◽  
Potential Benefits ◽  
System Properties ◽  
The Mathematical Model

The ship production process is a complex manufacturing system involving numerous working stations mutually interconnected by transport devices and buffers. Such a production system can be efficiently modeled using the stochastic system approach and Markov chains. Once formulated, the mathematical model enables analysis of the governing production system properties like the production rate, work-in-process, and probabilities of machine blockage and starvation that govern the production system bottleneck identification and its continuous improvement. Although the continuous improvement of the production system is a well-known issue, it is usually based on managerial intuition or more complex discrete event simulation yielding sub-optimal results. Therefore, a semi-analytical procedure for the improvability analysis using the Markov chain framework is presented in this paper in the case of the shipyard’s fabrication lines. Potential benefits for the shipyards are pointed out as the main gain of the improvability analysis.

scholarly journals A Methodology to Adapt and Understand a Manufacturing System and Operations using Discrete-Event Simulatio

2019 ◽  
Vol 8 (6) ◽  
pp. 4998-5003
Keyword(s):  
Discrete Event Simulation ◽  
Manufacturing Industry ◽  
Manufacturing System ◽  
Discrete Event ◽  
The State ◽  
State Variables ◽  
Event Simulation ◽  
Potential Benefits ◽  
Short Hand

Discrete-Event Simulation (DES) is concerned with system and modeling of that system, where the state of the system is transformed at different discrete points from time to time, and several event occurs from time to time and the changes in state variables will transform then activities/attributes connected to these state variables changes according to the event. It is a robust methodology in the manufacturing industry for strategic, tactical, and operational applications for an organization, and yet organizations ignore to use simulation and do not rely on it. Moreover, companies that are using DES are not using the potential benefits but merely used as a short-hand basis for problems like bottlenecks, optimization, and in later stages of production like PLM, this paper aims to apply and analyze Discrete-Event Simulation through a Manufacturing System. The work describes here is to understand the concept of simulation for a system and to practice Discrete Event methodology

The Environmental Impact Assessment of a Company’s Manufacturing System

2015 ◽  
Author(s):  
Dimitrios Anagnostakis ◽  
James M. Ritchie ◽  
Theodore Lim ◽  
Conor Craig ◽  
Jamie Speedie
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Production System ◽  
Manufacturing System ◽  
Discrete Event ◽  
Event Simulation ◽  
System A ◽  
Ideal System ◽  
Save Energy ◽  
A Company

The major objective of this study is the estimation of the environmental impacts of a company’s manufacturing system. For this purpose, environmental key performance indicators are selected related to the energy consumption and pollutant gas emissions. To obtain accurate results and achieve an evaluation of the production system, a discrete event simulation tool was equipped. In this way, the production processes of a company were modelled and simulated in order to be assessed with regards to their environmental performance and impacts. The assessment of the investigated manufacturing system was carried out, by comparing it against a hypothetical ideal system of 100% efficiency in order for potential reductions in energy consumption and carbon emissions to be identified. Additionally, a supplementary use of the proposed methodology is presented showing that modelling the production system in advance a company can save energy and associated costs as well as reduce carbon emissions.

scholarly journals Measuring lean implementation for maintenance service companies

2016 ◽  
Vol 7 (1) ◽  
pp. 35-61 ◽  
Author(s):  
Stephan J. de Jong ◽  
Wouter W.A. Beelaerts van Blokland
Keyword(s):  
Transaction Cost ◽  
Discrete Event Simulation ◽  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Discrete Event ◽  
Asset Specificity ◽  
Lean Implementation ◽  
Content Type ◽  
Event Simulation ◽  
Maintenance Service

Purpose – Implementation of lean manufacturing is currently performed in the production industry; however, for the airline maintenance service industry, it is still in its infancy. Indicators such as work in process, cycle time, on-time performance and inventory are useful indicators to measure lean implementation; however, a financial economic perspective taking fixed assets into consideration is still missing. Hence, the purpose of this paper is to propose a method to measure lean implementation from a fixed asset perspective for this type of industry. With the indicators, continuous improvement scenarios can be explored by value stream discrete event simulation. Design/methodology/approach – From literature, indicators regarding asset specificity to measure lean implementation are found. These indicators are analysed by a linear least square method to know if variables are interrelated to form a preliminary model. The indicators are tested by value stream-based discrete event simulation regarding continuous improvement scenarios. Findings – With the new found lean transaction cost efficiency indicators, namely, turnover, gross margin and inventory pre-fixed asset (T/FA, GM/FA and I/FA, respectively), it is possible to measure operation performance from an asset specificity perspective under the influence of lean implementation. Secondly, the results of implementing continuous improvement scenarios are measured with the new indicators by a discrete event simulation. Research limitations/implications – This research is limited to the airline maintenance, repair and overhaul (MRO) service industry regarding component repair. Further research is necessary to test the indicators regarding other airline MRO service companies and other sectors of complex service industries like health care. Practical implications – The lean transaction cost efficiency model provides the capability for a maintenance service company to simulate the effects of process improvements on operation performance for service-based companies prior to implementation. Social/implications – Simulation of a Greenfield process can involve employees with possible changes in processes. This approach supports the adoption of anticipated changes. Originality/value – The found indicators form a preliminary model, which contributes to the usage and linkage of theories on lean manufacturing and transaction cost theory – asset specificity.

scholarly journals CONWIP versus POLCA: A comparative analysis in a high-mix, low-volume (HMLV) manufacturing environment

2016 ◽  
Vol 9 (2) ◽  
pp. 432 ◽  
Author(s):  
Todd Frazee ◽  
Charles Standridge
Keyword(s):  
Discrete Event Simulation ◽  
Lead Time ◽  
Manufacturing Systems ◽  
Discrete Event ◽  
Model Verification ◽  
Manufacturing Environment ◽  
Event Simulation ◽  
Work In Process ◽  
Low Volume ◽  
Average Lead

Purpose: Few studies comparing manufacturing control systems as they relate to high-mix, low-volume applications have been reported. This paper compares two strategies, constant work in process (CONWIP) and Paired-cell Overlapping Loops of Cards with Authorization (POLCA), for controlling work in process (WIP) in such a manufacturing environment. Characteristics of each control method are explained in regards to lead time impact and thus, why one may be advantageous over the other.Design/methodology/approach: An industrial system in the Photonics industry is studied. Discrete event simulation is used as the primary tool to compare performance of CONWIP and POLCA controls for the same WIP level with respect to lead time. Model verification and validation are accomplished by comparing historic data to simulation generated data including utilizations. Both deterministic and Poisson distributed order arrivals are considered. Findings: For the system considered in this case study, including order arrival patterns, a POLCA control can outperform a CONWIP parameter in terms of average lead time for a given level of WIP. At higher levels of WIP, the performance of POLCA and CONWIP is equivalent. Practical Implications: The POLCA control helps limit WIP in specific áreas of the system where the CONWIP control only limits the overall WIP in the system. Thus, POLCA can generate acceptably low lead times at lower levels of WIP for conditions equivalent to the HMLV manufacturing systems studied.Originality/value: The study compliments and extends previous studies of  CONWIP and POLCA performance to a HMLV manufacturing environment. It demonstrates the utility of discrete event simulation in that regard. It shows that proper inventory controls in bottleneck áreas of a system can reduce average lead time.

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