Controlling the work-in-process in a tandem manufacturing system by hedging point policy

2015 ◽  
pp. 315-319
Author(s):  
Minru Zhu
Keyword(s):  
Manufacturing System ◽  
Work In Process ◽  
Hedging Point Policy

Simultaneous Modular Product Scheduling and Manufacturing Cell Reconfiguration Using a Genetic Algorithm

2006 ◽  
Vol 128 (4) ◽  
pp. 984-995 ◽  
Author(s):  
Hegui Ye ◽  
Ming Liang
Keyword(s):  
Genetic Algorithm ◽  
Manufacturing System ◽  
Product Variety ◽  
Manufacturing Cost ◽  
Successful Implementation ◽  
Strong Impact ◽  
Reconfigurable Manufacturing ◽  
Product Variant ◽  
Modular Product ◽  
Work In Process

Modular product design can facilitate the diversification of product variety at a low cost. Reconfigurable manufacturing, if planned properly, is able to deliver high productivity and quick responsiveness to market changes. Together, the two could provide an unprecedented competitive edge to a manufacturing company. The production of a family of modular products in a reconfigurable manufacturing system often requires reorganizing the manufacturing system in such a way that each configuration corresponds to one product variant in the same family. The successful implementation of this strategy lies in proper scheduling of the modular product operations and optimal selection of a configuration for producing each product variant. These two issues are closely related and have a strong impact on each other. Nevertheless, they have often been treated separately, rendering inefficient, infeasible, and conflicting decisions. As such, an integrated model is developed to address the two problems simultaneously. The objective is to minimize the sum of the manufacturing cost components that are affected by the two planning decisions. These include reconfiguration cost, machine idle cost, material handling cost, and work-in-process cost incurred in producing a batch of product variants. Due to the combinatorial nature of the problem, a genetic algorithm (GA) is proposed to provide quick and near-optimal solutions. A case study is conducted using a steering column to illustrate the application of the integrated approach. Our computational experience shows that the proposed GA substantially outperforms a popular optimization software package, LINGO, in terms of both solution quality and computing efficiency.

System Reliability Estimation for a Manufacturing Network with Joint Buffers

2018 ◽  
Vol 25 (04) ◽  
pp. 1850020 ◽  
Author(s):  
Ping-Chen Chang ◽  
Chia-Chun Wu ◽  
Chin-Tan Lee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
System Reliability ◽  
Manufacturing System ◽  
Reliability Estimation ◽  
Experimental Result ◽  
Production Lines ◽  
Work In Process ◽  
Process Output ◽  
Manufacturing Network

This paper develops a Monte Carlo Simulation (MCS) approach to estimate the performance of a multistate manufacturing network (MMN) with joint buffers. In the MMN, products are allowed to be produced by two production lines with the same function to satisfy demand. A performance index, system reliability, is applied to estimate the probability that all workstations provide sufficient capacity to satisfy a specified demand and buffers possess adequate storage. The joint buffers with finite storage are considered in the MMN. That is, extra work-in-process output from different production lines can be stored in the same buffer. An MCS algorithm is proposed to generate the capacity state and to check the storage usage of buffers to evaluate whether the demand can be satisfied or not. System reliability of the MMN is estimated through this MCS algorithm. Besides, performability for demand pairs assigned to production lines can be obtained. A practical example of touch panel manufacturing system is used to demonstrate the applicability of the MCS approach. Experimental result shows that system reliability is overestimated when buffer storage is assumed to be infinite. Moreover, joint buffer for an MMN is more reliable than buffers are installed separately in different production lines.

scholarly journals Effect of routing flexibility on the performance of manufacturing system

2019 ◽  
Vol 7 (2) ◽  
pp. 133
Author(s):  
Mohammed Ali ◽  
Wasif Ullah Khan
Keyword(s):  
Manufacturing System ◽  
Initial Level ◽  
System Capacity ◽  
Routing Flexibility ◽  
Work In Process ◽  
Analysis Of Results ◽  
Part Sequencing ◽  
Four Levels ◽  
Time Resource ◽  
Load Conditions

This work presented in this paper is based on the simulation of the routing flexibility enabled manufacturing system. In this study four levels of each factor (i.e. routing flexibility, system load conditions, system capacity and four part sequencing rules) are considered for the investigation. The performance of the routing flexibility enabled manufacturing system (RFEMS) is evaluated using three performance measures like make-span time, resource utilization and work-in-process. The analysis of results shows that the performance of the manufacturing system may be improved by adding in routing flexibility at the initial level along with other factors. However, the benefit of this flexibility diminishes at higher levels of routing flexibilities.

scholarly journals Modeling and analysis of carousel-based mixed-model flexible manufacturing system using colored Petri net

2019 ◽  
Vol 11 (12) ◽  
pp. 168781401988974
Author(s):  
Hafiz Zahid Nabi ◽  
Tauseef Aized
Keyword(s):  
Petri Net ◽  
System Performance ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Mixed Model ◽  
Colored Petri Net ◽  
Material Supply ◽  
Work In Process ◽  
Production Resources

This study aims to model, analyze, and evaluate performance of a flexible manufacturing system, constituting a carousel-based manufacturing and assembly cells layout, configured to produce mixed-model multiple products employing inter-/intra-cellular routing flexibility in which manufacturing and assembly resources are subject to working and failure modes. A hierarchical colored Petri net model is developed to analyze performance of the flexible manufacturing system. Colored Petri net modeling experiments have been conducted to evaluate the system performance for throughput, cycle time, and work-in-process. The system performance has been investigated in relation to material supply and handling system, process execution, and production resources reliability variables. Different input factors are considered for simulation modeling such as mean machining time, mean loading/unloading time, mean assembly time, buffer capacity, material supply inter-arrival time, number of operations between failures, and mean time to repair for production resources; a variation in input factors has shown a significant impact on system performance measures. The colored Petri net–based modeling, simulation, and analysis approach has been demonstrated as an efficient method for carousel-based mixed-model configured flexible manufacturing system.

Optimal Work-In-Process Inventory of Pull Type Manufacturing System

2021 ◽  
Author(s):  
Shih-Cheng Horng ◽  
Shieh-Shing Lin ◽  
Qi-Sheng Li
Keyword(s):  
Manufacturing System ◽  
Work In Process

Application of Lean Tool (Value Stream Mapping) in Minimisation of the Non-Value Added Waste (A Case Study of Tractor Industry)

2011 ◽  
Vol 110-116 ◽  
pp. 2062-2066 ◽  
Author(s):  
Paramdeep Singh ◽  
Harpuneet Singh
Keyword(s):  
Lean Manufacturing ◽  
Lead Time ◽  
Manufacturing System ◽  
Research Work ◽  
Value Added ◽  
Value Stream Mapping ◽  
Value Stream ◽  
Work In Process ◽  
Before And After ◽  
Traditional Manufacturing

Lean manufacturing has been proved to be an effective management philosophy for improving businesses in a competitive market by eliminating non-value added waste and improving in process operations. Value stream mapping is an important tool used to identify the opportunities for various lean techniques. The present research mainly focuses on the description of a model that is developed to contrast the “before” and “after” scenarios in detail in order to obtain the various benefits such as reduced production lead time, lower work in process inventory [1] and proper utilisation of the workforce. The current manufacturing system has been compared with the proposed pull (Kanban) system which shows the benefits of the proposed lean manufacturing system over the existing traditional manufacturing system. The present research work has been carried out at typical tractor industry which shows 50.5% reduction in total lead time in the future state value mapping of the crank case and the number of operators involved in processing of crank case has also been reduced from 22 to 18.

scholarly journals Human errors incorporation in work-in-process group manufacturing system

2017 ◽  
Vol 24 (4) ◽  
pp. 2050-2061 ◽  
Author(s):  
C.W. Kang ◽  
M. Ullah ◽  
B. Sarkar
Keyword(s):  
Manufacturing System ◽  
Human Errors ◽  
Work In Process ◽  
Process Group

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.

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