scholarly journals Scheduling for a Mold Die Production System in a Dynamic Environment. Effect of Dispatching Rule and Estimation of Due Date.

2001 ◽  
Vol 67 (655) ◽  
pp. 859-865
Author(s):  
Toshirou IYAMA ◽  
Masahiro MIZUNO ◽  
Rumi NOBE ◽  
Jyunnichi TAMAKI ◽  
Kenzou YAMAZAKI
Keyword(s):  
Production System ◽  
Dynamic Environment ◽  
Dispatching Rule ◽  
Due Date ◽  
Environment Effect

scholarly journals ANALISA PERBANDINGAN PENJADWALAN PRODUKSI DENGAN METODE CDS (CAMPBELL DUDEK SMITH), EDD (EARLIEST DUE DATE) DAN FCFS (FIRST COME FIRST SERVE) PADA PT. SARI WARNA ASLI UNIT V

2021 ◽  
Vol 1 (2) ◽  
pp. 46-51
Author(s):  
Dwi Ayu Lestari, Vikha Indira Asri
Keyword(s):  
Production Process ◽  
Production System ◽  
Production Scheduling ◽  
Job Shop ◽  
Allocation Of Resources ◽  
Due Date ◽  
Scheduling System ◽  
Make To Order ◽  
First Come First Serve ◽  
Scheduling Method

Scheduling is defined as the process of sequencing the manufacture of a product as a whole on several machines. All industries need proper scheduling to manage the allocation of resources so that the production system can run quickly and precisely as of it can produce optimal product. PT. Sari Warna Asli Unit V is one of the companies that implements a make to order production system with the FCFS system. Thus, scheduling the production process at this company is also known as job shop production scheduling. The methods used in this research are the CDS method, the EDD method and the FCFS method. The purpose of this research is to minimize the production time and determine the best method that can be applied to the company. The results of this research showed that the makespan obtained in the company's scheduling system with FCFS rules was 458 minutes, and the results of scheduling using the CDS method obtained a makespan value of 329 minutes, then the best production scheduling method that had the smallest makespan value was the CDS method.

Transient States of Cyclic Production Planning and Control

2014 ◽  
Vol 657 ◽  
pp. 961-965 ◽  
Author(s):  
Damian Krenczyk ◽  
Bożena Skołud
Keyword(s):  
Production System ◽  
Sufficient Conditions ◽  
Production Planning And Control ◽  
Dispatching Rule ◽  
Simulation Experiments ◽  
Planning And Control ◽  
Production Order ◽  
Verification Process ◽  
And Control ◽  
Transient Phases

The method for determining dispatching rules for transient phases, based on designation of a local dispatching rule for steady state, which determines the rest of its components has been presented in the paper. The algorithm for determining the transient rules has been presented and dependencies resulting from the presented sufficient conditions have been formulated. For the proposed transitional-rules generation algorithm the simulation model has been prepared. Simulation experiments to verify the correctness and effectiveness of the presented method have been conducted. The experiments have been prepared for input data describing the production system and the production order. In the verification process Enterprise Dynamics computer simulation system has been used. The results were compared with the results obtained for transitional phases realized through the S0 state of the production system.

scholarly journals Failure Rate Estimation in a Dynamic Environment

2015 ◽  
Vol 30 (1) ◽  
pp. 1-8
Author(s):  
Evans Gouno ◽  
Lise Guérineau
Keyword(s):  
Cox Model ◽  
Dynamic Environment ◽  
Simulated Data ◽  
Maximum Likelihood Estimates ◽  
Model Parameters ◽  
Time To Failure ◽  
Environment Effect ◽  
Testing Procedures ◽  
Stress Maximum ◽  
Piecewise Exponential Distribution

AbstractWe present a method to assess the reliability of a material operating in a dynamic environment. The dynamic environment is represented as a sequence of shocks governed by a self-exciting point process. The time-to-failure of the material is assumed to have a piecewise exponential distribution. A Cox model is integrated to take into account the effect of the stress. Maximum likelihood estimates of the model parameters are obtained and their properties are studied through simulated data. An application on field data is displayed. Hypothesis testing procedures for environment effect are suggested.

A New Combined Dispatching Rule of One-of-a-Kind Assembly Production Process

2011 ◽  
Vol 148-149 ◽  
pp. 409-412
Author(s):  
Ming Li ◽  
Ming Yu Zhang ◽  
Jun Han
Keyword(s):  
Performance Analysis ◽  
Production Process ◽  
Production System ◽  
Numerical Experiments ◽  
Critical Path ◽  
Total Tardiness ◽  
Dispatching Rule ◽  
Process Route ◽  
Interarrival Times ◽  
Assembly Production

In this paper, we researched a one-of-a-kind assembly production system where every product is unique (i.e. each product has its unique tree-like process route) and arrives one by one randomly with the exponentially distributed interarrival times. We proposed a new effective combined dispatching rule (ELFT rule) that is constructed by considering three factors: the latest finishing time (LFT), the remaining path size (RPS) and whether an operation is on the critical path (CP). We did many numerical experiments to compare the efficiency between the proposed rule and other rules that were reported in existing studies such as LFT rule and EDD rule. The performance analysis shows that the proposed dispatching rule is more effective in reducing the number of tardy products and total tardiness time.

Revenue management approach to due date quoting and scheduling in an assemble-to-order production system

OR Spectrum ◽  
2015 ◽  
Vol 37 (4) ◽  
pp. 951-982 ◽  
Author(s):  
Hendrik Guhlich ◽  
Moritz Fleischmann ◽  
Raik Stolletz
Keyword(s):  
Revenue Management ◽  
Production System ◽  
Management Approach ◽  
Due Date

Data Analytics in der Produktionsplanung*/Data analytics for production planning

2019 ◽  
Vol 109 (04) ◽  
pp. 232-236
Author(s):  
M. Veigt ◽  
B. Staar ◽  
S. Schukraft ◽  
M. Freitag
Keyword(s):  
Production Planning ◽  
Production System ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Industrie 4.0 ◽  
Manufacturing Companies ◽  
Due Date ◽  
Factors Influencing

Durch die Digitalisierung im Kontext von Industrie 4.0 steigen die Datenmengen in produzierenden Unternehmen an. Data-Analytics-Methoden erlauben es, automatisiert Muster in diesen Daten zu erkennen, die Rückschlüsse auf die Leistungsfähigkeit des Produktionssystems geben. Der Beitrag beschreibt, wie sich Data-Analytics-Methoden nutzen lassen, um Einflussfaktoren auf die Termintreue zu identifizieren. Für die Evaluation werden die Produktionsdaten eines mittelständischen Prototypenfertigers analysiert.   With digitization in the context of industry 4.0 the data volumes in manufacturing companies are increasing. Data analytics methods allow to automatically identify patterns in these data, providing insights into the performance of the production system. This article describes how these methods can be used to identify factors influencing the due date adherence. The data of a medium-sized prototype manufacturer are used for evaluation.

An Efficient Dispatching Rule in One-of-a-Kind Assembly Production

2012 ◽  
Vol 452-453 ◽  
pp. 432-436
Author(s):  
Ming Li ◽  
Ji Hua Cao
Keyword(s):  
Performance Analysis ◽  
Production System ◽  
Numerical Experiments ◽  
Critical Path ◽  
Total Tardiness ◽  
Dispatching Rule ◽  
Arrival Times ◽  
Process Route ◽  
Assembly Production

In this paper, we researched a one-of-a-kind assembly production system where every product is unique (i.e. each product has its unique tree-like process route) and arrives one by one randomly with the exponentially distributed inter arrival times. We proposed a new effective combined dispatching rule (LFD/RPS/CP rule) that is constructed by considering three factors: the latest finishing date (LFD), the remaining path size (RPS) and whether an operation is on the critical path (CP). We did many numerical experiments to compare the efficiency between the proposed rule and other rules that were reported in existing studies such as LFD rule and EDD rule. The performance analysis shows that the proposed dispatching rule is more effective in reducing the number of tardy products and total tardiness time.

scholarly journals Assessing leanness level with demand dynamics in a multi-stage production system

2016 ◽  
Vol 27 (5) ◽  
pp. 614-639 ◽  
Author(s):  
Rehab Ali ◽  
Ahmed Deif
Keyword(s):  
Production System ◽  
Production Management ◽  
Dynamic Environment ◽  
Content Type ◽  
Means Testing ◽  
Multi Stage ◽  
Management Policies ◽  
Demand Variation ◽  
Demand Variability ◽  
The Impact

Purpose – The purpose of this paper is to present a dynamic model to measure the degree of system’s leanness under dynamic demand conditions using a novel integrated metric. Design/methodology/approach – The multi-stage production system model is based on a system dynamics approach. The leanness level is measured using a new developed integrated metric that combines efficiency, WIP performance as well as service level. The analysis includes design of experiment technique at the initial analysis to examine the most significant parameters impacting the leanness score and then followed by examining different dynamic demand scenarios. Two scenarios were examined: one focussed low demand variation with various means (testing the impact of demand volumes) while the second focussed on high demand variation with constant means (testing the impact of demand variability). Findings – Results using the data from a real case study indicated that given the model parameters, demand rate has the highest impact on leanness score dynamics. The next phase of the analysis thus focussed on investigating the effect of demand dynamics on the leanness score. The analysis highlighted the different effects of demand variability and volumes on the leanness score and its different components leading to various demand and production management recommendations in this dynamic environment. Research limitations/implications – The presented lean management policies and recommendations are verified within the scope of similar systems to the considered company in terms of manufacturing settings and demand environment. Further research will be carried to extend the dynamic model to other dynamic manufacturing and service settings. Practical implications – The developed metric can be used not only to assess the leanness level of the systems which is very critical to lean practitioners but also can be used to track lean implementation progress. In addition, the presented analysis outlined various demand management as well as lean implementation policies that can improve the system leanness level and overall performance. Originality/value – The presented research develops a novel integrated metric and adds to the few literature on dynamic analysis of lean systems. Furthermore, the conducted analysis revealed some new aspects in understanding the relation between demand (variability and volume) and the leanness level of the systems. This will aid lean practitioners to set better demand and production management policies in today’s dynamic environment as well as take better decisions concerning lean technology investments.

Sign in / Sign up

Export Citation Format

Share Document