scholarly journals Innovative System for Scheduling Production Using a Combination of Parametric Simulation Models

2021 ◽  
Vol 13 (17) ◽  
pp. 9518
Author(s):  
Branislav Micieta ◽  
Jolanta Staszewska ◽  
Matej Kovalsky ◽  
Martin Krajcovic ◽  
Vladimira Binasova ◽  
...  
Keyword(s):  
Production System ◽  
Production Scheduling ◽  
Production Systems ◽  
Communication Channels ◽  
Simulation Models ◽  
Optimization Methods ◽  
Ratio Method ◽  
Critical Ratio ◽  
Scheduling Problems ◽  
Innovative System

The article deals with the design of an innovative system for scheduling piece and small series discrete production using a combination of parametric simulation models and selected optimization methods. An innovative system for solving production scheduling problems is created based on data from a real production system at the workshop level. The methodology of the innovative system using simulation and optimization methods deals with the sequential scheduling problem due to its versatility, which includes several production systems and due to the fact that in practice, several modifications to production scheduling problems are encountered. Proposals of individual modules of the innovative system with the proposed communication channels have been presented, which connect the individual elements of the created library of objects for solving problems of sequential production scheduling. With the help of created communication channels, it is possible to apply individual parameters of a real production system directly to the assembled simulation model. In this system, an initial set of optimization methods is deployed, which can be applied to solve the sequential problem of production scheduling. The benefit of the solution is an innovative system that defines the content of the necessary data for working with the innovative system and the design of output reports that the proposed system provides for production planning for the production shopfloor level. The DPSS system works with several optimization methods (CR—Critical Ratio, S/RO—Slack/Remaining Operations, FDD—Flow Due Date, MWKR—Most Work Remaining, WSL—Waiting Slack, OPFSLK/PK—Operational Flow Slack per Processing Time) and the simulation experiments pove that the most suitable solution for the FT10 problem is the critical ratio method in which the replaceability of the equipment was not considered. The total length of finding all solutions by the DPSS system was 1.68 min. The main benefit of the DPSS system is the combination of two effectively used techniques not only in practice, but also in research; the mentioned techniques are production scheduling and discrete computer simulation. By combining techniques, it is possible to generate a dynamically and interactively changing simulated production program. Subsequently, it is possible to decide in the emerging conditions of certainty, uncertainty, but also risk. To determine the conditions, models of production systems are used, which represent physical production systems with their complex internal processes. Another benefit of combining techniques is the ability to evaluate a production system with a number of emerging problem modifications.

scholarly journals A COMPARATIVE STUDY OF THE USABILITY OF DIFFERENT PRODUCTION SCHEDULING ALGORITHMS AND RULES

2021 ◽  
Vol 2 ◽  
pp. 41-46
Author(s):  
Pavol Jurík
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Job Shop ◽  
Flow Shop ◽  
Production Systems ◽  
Scheduling Problems ◽  
History Of ◽  
Service Object ◽  
The Right ◽  
Production Plans

Production scheduling optimization is a very important part of a production process. There are production systems with one service object and systems with multiple service objects. When using several service objects, there are systems with service objects arranged in a parallel or in a serial manner. We also distinguish between systems such as flow shop, job shop, open shop and mixed shop. Throughout the history of production planning, a number of algorithms and rules have been developed to calculate optimal production plans. These algorithms and rules differ from each other in the possibilities and conditions of their application. Since there are too many possible algorithms and rules it is not easy to select the proper algorithm or rule for solving a specific scheduling problem. In this article we analyzed the usability of 33 different algorithms and rules in total. Each algorithm or rule is suitable for a specific type of problem. The result of our analysis is a set of comparison tables that can serve as a basis for making the right decision in the production process decision-making process in order to select the proper algorithm or rule for solving a specific problem. We believe that these tables can be used for a quick and easy selection of the proper algorithm or rule for solving some of the typical production scheduling problems.

scholarly journals An Analysis of Research Trends in the Sustainability of Production Palnning

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 483
Author(s):  
Mohamed Saeed khaled ◽  
Ibrahim Abdelfadeel Shaban ◽  
Ahmed Karam ◽  
Mohamed Hussain ◽  
Ismail Zahran ◽  
...  
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Systems ◽  
Lot Sizing ◽  
Raw Materials ◽  
Social Indicators ◽  
Sustainable Production ◽  
Future Research ◽  
Scheduling Problems ◽  
Planning Problems

Sustainability has become of great interest in many fields, especially in production systems due to the continual increase in the scarcity of raw materials and environmental awareness. Recent literature has given significant attention to considering the three sustainability pillars (i.e., environmental, economic, and social sustainability) in solving production planning problems. Therefore, the present study conducts a review of the literature on sustainable production planning to analyze the relationships among different production planning problems (e.g., scheduling, lot sizing, aggregate planning, etc.) and the three sustainability pillars. In addition, we analyze the identified studies based on the indicators that define each pillar. The results show that the literature most frequently addresses production scheduling problems while it lacks studies on aggregate production planning problems that consider the sustainability pillars. In addition, there is a growing trend towards obtaining integrated solutions of different planning problems, e.g., combining production planning problems with maintenance planning or energy planning. Additionally, around 45% of the identified studies considered the integration of the economic and the environmental pillars in different production planning problems. In addition, energy consumption and greenhouse gas emissions are the most frequent sustainability indicators considered in the literature, while less attention has been given to social indicators. Another issue is the low number of studies that have considered all three sustainability pillars simultaneously. The finidings highlight the need for more future research towards holistic sustainable production planning approaches.

scholarly journals A review of energy-efficient scheduling in intelligent production systems

2019 ◽  
Vol 6 (2) ◽  
pp. 237-249 ◽  
Author(s):  
Kaizhou Gao ◽  
Yun Huang ◽  
Ali Sadollah ◽  
Ling Wang
Keyword(s):  
Energy Efficiency ◽  
Production Scheduling ◽  
Energy Cost ◽  
Energy Efficient ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Future Research ◽  
Scheduling Problems ◽  
Improve Energy Efficiency ◽  
Energy Efficient Scheduling

Abstract Recently, many manufacturing enterprises pay closer attention to energy efficiency due to increasing energy cost and environmental awareness. Energy-efficient scheduling of production systems is an effective way to improve energy efficiency and to reduce energy cost. During the past 10 years, a large amount of literature has been published about energy-efficient scheduling, in which more than 50% employed swarm intelligence and evolutionary algorithms to solve the complex scheduling problems. This paper aims to provide a comprehensive literature review of production scheduling for intelligent manufacturing systems with the energy-related constraints and objectives. The main goals are to summarize, analyze, discuss, and synthesize the existing achievements, current research status, and ongoing studies, and to give useful insight into future research, especially intelligent strategies for solving the energy-efficient scheduling problems. The scope of this review is focused on the journal publications of the Web of Science database. The energy efficiency-related publications are classified and analyzed according to five criteria. Then, the research trends of energy efficiency are discussed. Finally, some directions are pointed out for future studies.

scholarly journals Case Study of Building a Digital Twin for a Production System

2021 ◽  
Vol 29 (49) ◽  
pp. 51-58
Author(s):  
Fedor Burčiar ◽  
Pavel Važan ◽  
Simona Pulišová
Keyword(s):  
Production System ◽  
Industry 4.0 ◽  
Production Systems ◽  
Simulation Models ◽  
Cyber Physical Systems ◽  
Production Data ◽  
Physical Systems ◽  
Production Processes ◽  
Gathering Data

Abstract As the term of Industry 4.0 becomes more and more relevant with each passing day, it is up to researchers and companies to find solutions to integrating all the technologies it covers. One of those technologies, even though not highly developed, is simulation and building Cyber-Physical Systems for gathering data and improving the production processes. In the research described in this paper, we focused on integrating production data with simulation models in order to make the process of understanding and learning about complex production systems as simple and as quick as possible. This paper contains three sections. The first one introduces the theoretical fundamentals of our research. The second one focuses on the methods used to create a digital model of production system. The final one discusses the results of the conducted experiments, and their impact on further research.

Automatic Generation Method of Simulation Model for Production Planning and Simulation Systems Integration

2014 ◽  
Vol 1036 ◽  
pp. 825-829 ◽  
Author(s):  
Damian Krenczyk
Keyword(s):  
Production Planning ◽  
Production System ◽  
Production Systems ◽  
Computer Software ◽  
Simulation Models ◽  
Automatic Generation ◽  
System Structure ◽  
Dynamics Simulation ◽  
Flow Topology ◽  
Simulation Systems

In the paper the method of integration of production planning and simulation systems has been presented. An automatic generation method of production systems models has been implemented to integrate the Production Order Verification System (SWZ) for multi-assortment, concurrent production planning) and Enterprise Dynamics simulation system. Submitted methodology allowed the direct generation of simulation models for production systems with the use of data obtained from PPC systems, regardless of the production system structure, flow topology of the production processes and the amount of resources and production orders. Generation of simulation models is performed automatically, allowing the omission of time-and labor-consuming process of building a simulation. In the process of generation of the simulation models, methods of data mapping, transformation and exchange, between heterogeneous computer systems (PPC/DES) using neutral formats and data storing (XML) in conjunction with an intermediate neutral data model have been used. The result of transformation is the input file for simulation systems, containing information about the production system model, together with control procedures. Based on the described methodology, operation algorithms have been developed and the computer software RapidSim, that integrates PPC and DES systems has been presented.

Analysis and Simulation Methods of the Mechanisms for the Innovational Development

2019 ◽  
pp. 16-33
Author(s):  
Marta K. Isaeva
Keyword(s):  
Production Systems ◽  
Technological Development ◽  
Computer Experiment ◽  
Simulation Models ◽  
Construction Simulation ◽  
Technological Structure ◽  
Research Sector ◽  
Practical Trial ◽  
Construction Model ◽  
Computation Analysis

The paper dedicates in commemoration of K.A. Bagrinovsky, known scientist, doctor of economic sciences, professor. His thesis was theoretic problems of mathematical modeling and operation of economy. His works in the operations research, the methods making decision, the simulation were received in scientific world. The analysis and the modeling of the mechanisms for scientific and technological development for the production systems of different level in economic hierarchic both centrally controlled economy and making mechanism were conduced by Bagrinovsky in CEMI RAS. The paper presents the investigations (2001–2015) of the analysis and the simulation of the different mechanisms of the innovational activity. It also discusses the methods of the development the complex of the simulation models. In a sense simulation modeling is the science and the art as the selection of the salient parameters for the construction model, intake simplification, the computer experiment and the making decision based on scarcity of accuracy models rest on the heuristic power of men: the practical trial, the intelligence and the intuition. K.A. Bagrinovsky introduced the considerable endowment in the development of this direction for economic and mathematical investigation.The principal object was to show that the relationship between the innovational policy and the technological structure, scientific research sector and the introducing of the progressive production and the organizational structure is obtainable by the models. The character of these relationships may be to use in control of the parameters for the modernization economic. The construction simulation models and the experimental computation analysis were presented the investigations the different mechanisms of the innovational development ant the variants of the estimation have been accomplished on the modeling level by the computer experiment.

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.

Optimization methods for power scheduling problems in smart home: Survey

2019 ◽  
Vol 115 ◽  
pp. 109362 ◽  
Author(s):  
Sharif Naser Makhadmeh ◽  
Ahamad Tajudin Khader ◽  
Mohammed Azmi Al-Betar ◽  
Syibrah Naim ◽  
Ammar Kamal Abasi ◽  
...  
Keyword(s):  
Smart Home ◽  
Optimization Methods ◽  
Scheduling Problems ◽  
Power Scheduling

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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