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.

Production Orders Sequencing in Mixed-Model Assembly Lines

2014 ◽  
Vol 657 ◽  
pp. 359-363
Author(s):  
Marcin Zemczak
Keyword(s):  
Mixed Model ◽  
Production Capacity ◽  
Approximate Solutions ◽  
New Order ◽  
Task Sequence ◽  
Optimal Method ◽  
Sequencing Problem ◽  
Car Sequencing ◽  
Method Of Solution ◽  
Production Orders

The paper presents the production orders sequencing 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 research, the sequencing problem considered in the paper, may be denoted as CSP (Car Sequencing Problem) and belongs to the NP-hard class, as has been proven by simple reduction from Hamiltonians Path problem [1]. Optimal method of solution has not yet been found, therefore only approximate solutions have been offered [2]. Approximate solutions are based mainly on the evolutionary algorithms. However certain problems, as lack of possibility to check the effectiveness of the solution or the possibility to reach twice the same solution are observed. Regardless of the structure of specific assembly system, while considering reception of new tasks into the execution, current review of the state of the system is obligatory in order to decide whether, when and which new order can be accepted for assembly. 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.

Application of Graph Theory for Production Orders Sequencing in Mixed-Model Production Systems

2015 ◽  
Vol 809-810 ◽  
pp. 1343-1347
Author(s):  
Marcin Zemczak ◽  
Bożena Skołud ◽  
Damian Krenczyk
Keyword(s):  
Production Management ◽  
Mixed Model ◽  
Production Systems ◽  
Assembly Systems ◽  
Optimal Method ◽  
Car Sequencing ◽  
Linear Assembly ◽  
Method Of Solution ◽  
Hard Problems ◽  
Production Orders

In this paper, problem of sequencing of production orders in mixed-model assembly systems is being analysed. The sequencing in such system is mostly addressed as a CSP problem (Car Sequencing Problem) and due to the fact that no optimal method of solution has yet been found it belongs to the NP-hard problems [1,2]. The NP-hardness of the problem has been proven in [3]. The problem connected with proper sequencing arises from the fact that nowadays it’s the clients who have the biggest influence on the sellers offer. The possibility to customize almost each and every product complicates the production management, as instead of having 10 different products, the number of them may grow up to few hundreds [4]. The problem may be especially observed in automotive industry, however recently it may be also met in household appliances industry, as mass customization can be also observed on that market. Each product may differ in labor-effectiveness, and due to the fact of carrying the assembly in linear assembly systems, each unevenness, each transgression of takt time on a single work-station may lead to the line stoppage.

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.

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