Dynamic Maintenance Strategy With Q-Learning for Workstations in a Flow Line Manufacturing System

2010 ◽  
Author(s):  
Sagar Kamarthi ◽  
Abe Zeid ◽  
Yusuf Ozbek
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flow Line ◽  
Maintenance Cost ◽  
Q Learning ◽  
Intelligent Maintenance ◽  
Dynamic Maintenance ◽  
Maintenance Systems ◽  
Modern Manufacturing ◽  
Production Losses

Every machine or equipment in a manufacturing facility is subject to failure due to deterioration based on cumulative wear, crack growth, erosion, etc. This failure will cause production losses and delays resulting in high costs. As the modern manufacturing systems are getting more and more complex, intelligent maintenance schemes must replace the old labor intensive planned maintenance systems to ensure that equipment continues to function. If the maintenance decision is based on the state of the system rather than its age, this leads to the choice of a Condition Based Maintenance (CBM) policy to prevent catastrophic unexpected machine breakdowns and increase the availability of individual machines, but it also introduces randomness into the manufacturing operation. This paper presents a Q-Learning model to dynamically group maintenance actions on different machines and execute them simultaneously, so that one can reduce maintenance cost and increase the efficiency of the manufacturing system.

Real-Time Prognostic and Dynamic Maintenance Window Scheme for Reconfigurable Manufacturing Systems

2019 ◽  
Author(s):  
Yifan Dong ◽  
Tangbin Xia ◽  
Lei Xiao ◽  
Ershun Pan ◽  
Lifeng Xi
Keyword(s):  
Real Time ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Degradation Process ◽  
Maintenance Cost ◽  
Time To Failure ◽  
Reconfigurable Manufacturing Systems ◽  
Reconfigurable Manufacturing ◽  
Reconfigurable Manufacturing System ◽  
Dynamic Maintenance

Abstract Real-time condition acquisition and accurate time-to-failure (TTF) prognostic of machines are both crucial in the condition based maintenance (CBM) scheme for a manufacturing system. Most of previous researches considered the degradation process as a population-specific reliability characteristics and ignored the hidden differences among the degradation process of individual machines. Moreover, existing maintenance scheme are mostly focus on the manufacturing system with fixed structure. These proposed maintenance scheme could not be applied for the reconfigurable manufacturing system, which is quite adjustable to the various product order and customer demands in the current market. In this paper, we develop a systematic predictive maintenance (PM) framework including real-time prognostic and dynamic maintenance window (DMW) scheme for reconfigurable manufacturing systems to fill these gaps. We propose a real-time Bayesian updating prognostic model using sensor-based condition information for computing each individual machine’s TTFs, and a dynamic maintenance window scheme for the maintenance work scheduling of a reconfigurable manufacturing system. This enables the real-time prognosis updating, the rapid decision making for reconfigurable manufacturing systems, and the notable maintenance cost reduction.

Resilience Measures of Manufacturing Systems Under Disruptions

2014 ◽  
Author(s):  
Xi Gu ◽  
Xiaoning Jin ◽  
Jun Ni
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Production Condition ◽  
Unreliable Machines ◽  
System A ◽  
Multi Stage ◽  
Stage System ◽  
Normal Production ◽  
System Resilience ◽  
Production Losses

Unexpected disruptive events always interrupt normal production condition and cause production losses in the manufacturing system. A resilient system is capable of settling itself to the steady-state quickly after the disruption, and compensating for the lost production by using a relatively little overtime. In this paper, we define throughput settling time (TST) and overtime to recover (OTTR) as two resilience measures to analyze multi-stage serial-parallel systems with unreliable machines and finite intermediate buffers. We perform an exact analysis for a two-stage system and develop an approximation method for general multi-stage systems. Numerical case studies are conducted to investigate the system resilience under different configurations.

scholarly journals Model Terintegrasi Penjadwalan Batch dan Pm dengan Kriteria Minimalisasi Biaya Simpan, Setup dan Pm pada Mesin dengan Increasing Failure Rate

2013 ◽  
Vol 4 (1) ◽  
pp. 121
Author(s):  
Zahedi Zahedi
Keyword(s):  
Failure Rate ◽  
Preventive Maintenance ◽  
Product Life Cycle ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Flow Time ◽  
Maintenance Cost ◽  
Setup Cost ◽  
Increasing Failure Rate ◽  
Actual Flow

Development of today's manufacturing systems leads to the getting shorter in product life cycle, more variety of products, as well as increasing in consumer demand for quality and timeliness. Thus the accuracy and speed of decision-making within the manufacturing system becomes important. This paper proposes an integrated model of batch scheduling and preventive maintenance scheduling, in assumption no non-conforming parts to the criteria of minimizing the total saving cost, setup cost, preventive maintenance cost in minimizing the actual flow time on a machine with increasing failure rate. An example is provided to show how the model and algorithm work.

The Architecture and Development Environment of Virtual Manufacturing Systems

2000 ◽  
Author(s):  
Qing Ke Yuan ◽  
Xin Chen
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
International Market ◽  
Virtual Manufacturing ◽  
Manufacturing Industries ◽  
Development Environment ◽  
Perfect Performance ◽  
Effective Technology ◽  
Modern Manufacturing ◽  
The Times

Abstract For adapting the demands of the rapid changing and enhancing the competing capability of enterprise in the international market, various modern manufacturing systems have been put forward, which are aimed at various specifications, perfect performance and high quality, low production cost and short manufacturing cycle of products, virtual manufacturing system (VMS) has been emerged as the times require, which is effective technology to meet the challenge of 21 century’s manufacturing industries. Based on analyzing modern manufacturing systems, according to the characteristics and requirement of VMS, in this paper, the architecture, the key technologies and the implement way of VMS were explored, and development environment for VMS was put forward, which is a powerful tool for building VMS.

Intelligent Maintenance Systems and Predictive Manufacturing

2020 ◽  
Vol 142 (11) ◽  
Author(s):  
Jay Lee ◽  
Jun Ni ◽  
Jaskaran Singh ◽  
Baoyang Jiang ◽  
Moslem Azamfar ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Health Management ◽  
Global Market ◽  
Future Research ◽  
Management Tools ◽  
Maintenance Strategies ◽  
Market Growth ◽  
Intelligent Maintenance ◽  
Maintenance Systems

Abstract With continued global market growth and an increasingly competitive environment, manufacturing industry is facing challenges and desires to seek continuous improvement. This effect is forcing manufacturers to squeeze every asset for maximum value and thereby calls for high-equipment effectiveness, and at the same time flexible and resilient manufacturing systems. Maintenance operations are essential to modern manufacturing systems in terms of minimizing unplanned down time, assuring product quality, reducing customer dissatisfaction, and maintaining advantages and competitiveness edge in the market. It has a long history that manufacturers struggle to find balanced maintenance strategies without significantly compromising system reliability or productivity. Intelligent maintenance systems (IMS) are designed to provide decision support tools to optimize maintenance operations. Intelligent prognostic and health management tools are imperative to identify effective, reliable, and cost-saving maintenance strategies to ensure consistent production with minimized unplanned downtime. This article aims to present a comprehensive review of the recent efforts and advances in prominent methods for maintenance in manufacturing industries over the last decades, identifying the existing research challenges, and outlining directions for future research.

scholarly journals MODELING OF THE MANUFACTURING SYSTEMS STATE IN THE CONDITIONS OF THE LEAN PRODUCTION

2021 ◽  
Vol 2021 (2) ◽  
pp. 4408-4413
Author(s):  
KONSTANTIN DYADYURA ◽  
◽  
LIUDMYLA HREBENYK ◽  
TIBOR KRENICKY ◽  
TADEUSZ ZABOROWSKI ◽  
...  
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Large Time ◽  
Lean Production ◽  
Energy Materials ◽  
Markov Analysis ◽  
Time Varying Parameters ◽  
External Conditions ◽  
Modern Manufacturing ◽  
The Given

This article investigates the hierarchy of the manufacturing system, which consists of a set of interrelated processes aimed at converting information, knowledge, energy, materials, and other resources into value for the consumer based on the principles of lean production. Modern manufacturing systems are becoming more and more complex to manage. The problems that need to be solved are associated with a significant number of time-varying parameters, large time delays, high non-linearity of processes, and a complex relationship between input and output parameters. Depending on the parameters of internal components and characteristics of external conditions, the state of manufacturing systems can change in an unpredictable manner. The paper considers many types of discrete states in which the system can be. The estimation of the probability of finding the manufacturing system in any of the given states was carried out using discrete Markov analysis. The article also presents the results of studies of possible transitions between states in which the production system is presented in the form of a transition matrix.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

Introduction of Flexible Manufacturing Systems as a Necessary Measure for the Russian Industrial Development

2019 ◽  
Vol 957 ◽  
pp. 195-202 ◽  
Author(s):  
Elizaveta Gromova
Keyword(s):  
Flexible Manufacturing ◽  
Flexible Manufacturing Systems ◽  
Industrial Development ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Agile Manufacturing ◽  
Industrial Sector ◽  
Business Environment ◽  
Maximum Speed ◽  
Industrial Enterprises

With the onset of the Fourth Industrial Revolution, the business environment becomes inherent in changes that occur with maximum speed, as well as characterized by the systemic nature of the consequences. One of them is the transformation of operational management models in industrial enterprises. The modern manufacturing system should focus not only on speed of response and flexibility, but also on the cost and quality of products. Integration of effective models: agile manufacturing, quick response manufacturing and lean production, in order to extract the best from them is proposed. The purpose of this study is to analyze this flexible manufacturing system and to relate it to the current state of the Russian industrial development. Theoretical and practical aspects of this model are presented. The examples of the flexible models introduction in the Russian industrial sector is allocated. The conclusion about the necessity of the flexible manufacturing systems implementation for the Russian industrial development is drawn.

DECISION SUPPORT FOR A SUSTAINABLE PRODUCTION IN JOB SHOP MANUFACTURING SYSTEMS

10.6036/9917 ◽  
2021 ◽  
Vol 96 (5) ◽  
pp. 455-459
Author(s):  
MAHDI NADERI ◽  
ANTONIO FERNÁNDEZ ULLOA ◽  
JOSÉ ENRIQUE ARES GÓMEZ ◽  
GUSTAVO PELÁEZ LOURIDO
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Job Shop ◽  
Sustainable Production ◽  
Ease Of Use ◽  
Manufacturing Companies ◽  
Strategic Decisions ◽  
Production Environments

Despite the growing importance that is being given to the concepts of sustainability in many areas, not only in industry but also in the economy and public opinion in general, until now, most research has focused, practically, on the analysis of the concepts, but has not addressed, in a comprehensive way, its impact in decision making probably due to the complex relations of interdependence between its different aspects. In this context, MAPSAM (Methodology for the Assessment of Sustainability in Manufacturing Processes and Systems) was created to help the decision-making process, allowing a conscious and transparent assessment by administrators and managers at the different levels of the structure of companies and organisations. This article explains its development and application in a "job shop" type manufacturing system with an approach that allows the integration of economic, environmental and social criteria. MAPSAM is based on the use of various techniques and tools to quantify the importance of each aspect of sustainability and it has been applied in other production environments, being implemented in different systems, analysing their ease of use and evaluating their behaviour. The objective is to show how it helps to make operational, tactical and strategic decisions in the management on these type of manufacturing companies and, specifically, in this contribution we want to highlight its versatility and applicability, by validating it in a certain type of layout. With this new application, MAPSAM increases its possibilities as an innovative instrument that allows companies to make conscious and sustainable decisions in order to be more efficient, fair, supportive and respectful of the environment. Keywords: Manufacturing System, Simulation, Decision Support, Sustainable Production, Decision-Making

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