scholarly journals A Comparative Study of Unbalanced Production Lines Using Simulation Modeling: A Case Study for Solar Silicon Manufacturing

2022 ◽  
Vol 14 (2) ◽  
pp. 697
Author(s):  
Chen-Yang Cheng ◽  
Shu-Fen Li ◽  
Chia-Leng Lee ◽  
Ranon Jientrakul ◽  
Chumpol Yuangyai
Keyword(s):  
Cycle Time ◽  
Performance Optimization ◽  
Production System ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Optimization Technique ◽  
Production Lines ◽  
Work In Process ◽  
Pull Production ◽  
Solar Silicon

In the solar silicon manufacturing industry, the production time for crystal growth is ten times longer than at other workstations. The pre-processing time at the ingot-cutting station causes work-in-process (WIP) accumulation and an excessively long cycle time. This study aimed to find the most effective production system for reducing WIP accumulation and shortening the cycle time. The proposed approach considered pull production systems, and the response surface methodology was adopted for performance optimization. A simulation-based optimization technique was used for determining the optimal pull production system. The comparison between the results of various simulated pull production systems and those of the existing solar silicon manufacturing system showed that a hybrid production system in which a kanban station was installed before the bottleneck station with a CONWIP system incorporated for the rest of the production line could reduce the WIP volume by 26% and shorten the cycle time by 16% under the same throughput conditions.

System dynamics modelling of fixed and dynamic Kanban controlled production systems: a supply chain perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jagan Mohan Reddy K. ◽  
Neelakanteswara Rao A. ◽  
Krishnanand Lanka ◽  
PRC Gopal
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Cycle Time ◽  
Production System ◽  
Demand Uncertainty ◽  
Production Systems ◽  
Decision Variable ◽  
Content Type ◽  
Pull Production ◽  
Kanban System

Purpose Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty. Design/methodology/approach In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios. Findings From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible. Research limitations/implications In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size. Originality/value This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

Pull Production Systems

2021 ◽  
pp. 80-112
Author(s):  
Eduardo Guilherme Satolo ◽  
Milena Estanislau Diniz Mansur dos Reis ◽  
Robisom Damasceno Calado
Keyword(s):  
Decision Making ◽  
Hybrid Systems ◽  
Production System ◽  
Lean Manufacturing ◽  
Production Systems ◽  
Pull Production ◽  
Decision Making Processes ◽  
Pull Systems ◽  
Aid Decision ◽  
Pull Production System

This chapter aims to organize knowledge about pull production systems by presenting the underlying concepts of lean manufacturing as for its origin, principles, and relations with PPC. Pull production is one the fundamental principles of lean manufacturing, and its implementation can bring positive impacts. For such a purpose, sequential and mixed supermarket pull systems stand out in which the integration between pull production systems and PPC and its various levels is a main subject of discussion. The JIT model or Kanban method and hybrid systems, such as conwip and lung-drum-string theory, are mechanisms for managing pull production systems. Finally, a pull production system implementation is presented for illustration purposes. At the end of this chapter, it is expected that skills are developed by readers, which are going to assist them in using the tools presented to model production systems and aid decision-making processes.

scholarly journals Accuracy of Semi-Analytical and Numerical Approaches in the Evaluation of Serial Bernoulli Production Lines

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1461
Author(s):  
Viktor Ložar ◽  
Neven Hadžić ◽  
Tihomir Opetuk ◽  
Vedran Slapničar
Keyword(s):  
Performance Measures ◽  
Analytical Approach ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Numerical Approach ◽  
Production Lines ◽  
State Behavior ◽  
Finite State ◽  
State Method ◽  
Numerical Approaches

The manufacturing industry has a great impact on the economic growth of countries. It is, therefore, crucial to master the skills of the production system by mathematical tools that enable the evaluation of the production systems’ performance measures. Four mathematical approaches toward the modeling of steady-state behavior of serial Bernoulli production lines were considered in this study, namely, the analytical approach, the finite state method, the aggregation procedure, and numerical modeling. The accuracy of the performance measures determined using the semi-analytical methods and the numerical approach was validated using numerous theoretical examples and the results obtained using the analytical model. All of the considered methods demonstrated relevant reliability, regardless of the different theoretical backgrounds.

scholarly journals Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach

2018 ◽  
Vol 11 (1) ◽  
pp. 161 ◽  
Author(s):  
Aydin Torkabadi ◽  
Rene Mayorga
Keyword(s):  
Production System ◽  
Production Control ◽  
Control Strategies ◽  
Fuzzy Ahp ◽  
Control Policies ◽  
Work In Process ◽  
Multi Stage ◽  
Pull Production ◽  
Pull Control Policies ◽  
Stochastic Processing Times

Purpose: Just-In-Time (JIT) production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs) are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP), and a hybrid system, are evaluated by considering uncertainty.Design/methodology/approach: Multi-Criteria Decision Making (MCDM) methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP) and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method.Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system.Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand.Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.

scholarly journals Application of Semi-Analytical Methods in Production Systems Engineering

2020 ◽  
Vol 14 (3) ◽  
pp. 360-364
Author(s):  
Viktor Ložar ◽  
Filip Abdulaj ◽  
Tihomir Opetuk ◽  
Neven Hadžić ◽  
Hrvoje Cajner
Keyword(s):  
Systems Engineering ◽  
Production System ◽  
Analytical Approach ◽  
Production Systems ◽  
Numerical Approach ◽  
Paint Shop ◽  
Production Lines ◽  
Aggregation Method ◽  
Advantages And Disadvantages ◽  
Automotive Paint

Production lines can be designed by an analytical, semi-analytical, or numerical approach. This paper gives a brief introduction to the analytical approach of a single buffer line, the aggregation method, and the analytical approach of a multi-buffer line. An automotive paint shop production system will be used as a figurative example to compare the aggregation method and the recently developed analytical approach for a multi-buffer line. A discussion at the end will show the advantages and disadvantages of the analytical approach.

scholarly journals RELIABILITY ENGINEERING OF LARGE JIT PRODUCTION SYSTEMS

2012 ◽  
Vol 19 (03) ◽  
pp. 1250011 ◽  
Author(s):  
JOSE FARIA ◽  
EUSEBIO NUNES
Keyword(s):  
Production System ◽  
Production Systems ◽  
Structural Characteristics ◽  
Evaluation Framework ◽  
System Level ◽  
Reliability Engineering ◽  
Generalized Distributions ◽  
Work In Process ◽  
Failure Propagation ◽  
Jit Production

This paper introduces the rationale and the fundamental elements and algorithms of a reliability engineering methodology combining analytical and simulation tools, and discusses its application to the design of a large, multi-cell and heterogeneous production system with just-in-time (JIT) deliveries. In order to cope with the inherent complexity of such analysis, a two level hierarchical modeling and evaluation framework was developed. Local models are first obtained from the failure and repair processes of the manufacturing equipment. Then, these models are combined with the failure propagation delays introduced by the work-in-process buffers in order to obtain the system level model. The evaluation algorithm is able to deal with reliability models containing stochastic processes with generalized distributions. This fundamental requirement comes from the fact that repair and failure propagation processes typically present hyper-exponential distributions, e.g., lognormal distributions, that cannot be assessed using the conventional reliability techniques. The second part of the paper addresses several design issues of the production system that directly impact the reliability of the deliveries, and explains how the behavioral and structural characteristics of JIT production systems were explored in order to implement effective evaluation algorithms.

scholarly journals Implementation of lean manufacturing to reduce waste in production line with value stream mapping approach and Kaizen in division sanding upright piano, case study in: PT. X

2018 ◽  
Vol 154 ◽  
pp. 01095 ◽  
Author(s):  
W. A. Santosa ◽  
M. Sugarindra
Keyword(s):  
Cycle Time ◽  
Lean Manufacturing ◽  
Lead Time ◽  
Value Stream Mapping ◽  
Production Lines ◽  
Production Scale ◽  
Value Stream ◽  
Work In Process ◽  
Quality Product

PT. XY produces musical instruments such as Upright Pianos and Grand Pianos. Due to a competitive competition, a good quality product is highly required as well as increasing the production scale. To achieve these objectives, company needs to reduce wastes occurred in its production lines, particularly in the division of sanding panel upright piano (UP) which produces type of PE B1 pianos. High cycle time and lead-time are caused by wastes in UP panel sanding division. Therefore, it is needed improvements to be applied here so that the production lines will be run more effectively and efficiently. This study aims to identify wastes using Value Stream Mapping (VSM) as a tool of lean manufacturing and to implement the improvements using Kaizen. It is found that the wastes are motion and waiting. Furthermore, the improvements (kaizen) are focused on reducing motion and waiting wastes. It is shown that cycle time decreased from 51.16 minutes to 41.90 minutes, work in process or inventory can be reduced to 24 pcs over 32 pcs, and the lead-time is 0.167 days of 0.222 days.

scholarly journals Soil Bacterial Community Diversity and Composition as Affected by Tillage Intensity Treatments in Corn-Soybean Production Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 157-172
Author(s):  
Shankar G. Shanmugam ◽  
Normie W. Buehring ◽  
Jon D. Prevost ◽  
William L. Kingery
Keyword(s):  
Microbial Community ◽  
Bacterial Community ◽  
Community Composition ◽  
Production System ◽  
Soil Microbial Community ◽  
Production Systems ◽  
Bacterial Community Composition ◽  
Soybean Production ◽  
Soil Microbial ◽  
Soil Bacterial

Our understanding on the effects of tillage intensity on the soil microbial community structure and composition in crop production systems are limited. This study evaluated the soil microbial community composition and diversity under different tillage management systems in an effort to identify management practices that effectively support sustainable agriculture. We report results from a three-year study to determine the effects on changes in soil microbial diversity and composition from four tillage intensity treatments and two residue management treatments in a corn-soybean production system using Illumina high-throughput sequencing of 16S rRNA genes. Soil samples were collected from tillage treatments at locations in the Southern Coastal Plain (Verona, Mississippi, USA) and Southern Mississippi River Alluvium (Stoneville, Mississippi, USA) for soil analysis and bacterial community characterization. Our results indicated that different tillage intensity treatments differentially changed the relative abundances of bacterial phyla. The Mantel test of correlations indicated that differences among bacterial community composition were significantly influenced by tillage regime (rM = 0.39, p ≤ 0.0001). Simpson’s reciprocal diversity index indicated greater bacterial diversity with reduction in tillage intensity for each year and study location. For both study sites, differences in tillage intensity had significant influence on the abundance of Proteobacteria. The shift in the soil bacterial community composition under different tillage systems was strongly correlated to changes in labile carbon pool in the system and how it affected the microbial metabolism. This study indicates that soil management through tillage intensity regime had a profound influence on diversity and composition of soil bacterial communities in a corn-soybean production system.

Industrial internet of things for smart manufacturing applications using hierarchical trustful resource assignment

Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Duan Pingli ◽  
Bala Anand Muthu ◽  
Seifedine Nimer Kadry
Keyword(s):  
Internet Of Things ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
The Internet ◽  
Resource Assignment ◽  
Industrial Internet Of Things ◽  
Assignment Method ◽  
Industrial Internet

BACKGROUND: The manufacturing industry undergoes a new age, with significant changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices, which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. OBJECTIVES: The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. RESULTS: Finally, experimental findings demonstrate that when the IIoT equipment and gateways are valid, the utilities of each participant are improved. CONCLUSION: This is an easy and powerful method to guarantee that intelligent manufacturing components genuinely work for their purposes, which want to integrate each element into a system without interactions with each other.

A New Procedure of Production Orders Sequencing in Mixed-Model Production Systems

2014 ◽  
Vol 1036 ◽  
pp. 864-868 ◽  
Author(s):  
Marcin Zemczak ◽  
Damian Krenczyk
Keyword(s):  
Task Scheduling ◽  
Production System ◽  
Mixed Model ◽  
Production Systems ◽  
Production Capacity ◽  
Approximate Solutions ◽  
Task Sequence ◽  
Optimal Method ◽  
Sequencing Problem ◽  
Car Sequencing

The paper presents the task scheduling issue, which main aim is to establish a proper sequence of tasks, that would maximize the utilization of companys production capacity. According to the literature sources, the presented sequencing problem, denoted as CSP (Car Sequencing Problem) belongs to the NP-hard class, as has been proven by simple reduction from Hamiltonians Path problem. Optimal method of solution has not yet been found, only approximate solutions have been offered, especially from the range of evolutionary algorithms. Regardless of specific production system, while considering reception of new tasks into the system, current review of the state of the system is required in order to decide whether and when a new order can be accepted for execution. In this paper, the problem of task scheduling is limited to the specific existing mixed-model production system. The main goal is to determine the effective method of creation of task sequence. Through the use of computational algorithms, and automatic analysis of the resulting sequence, rates of production are able to be checked in a real time, and so improvements can be proposed and implemented.

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