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.

Study on Intelligent Maintenance Service Mechanism and Realization

2014 ◽  
Vol 644-650 ◽  
pp. 6355-6357
Author(s):  
Shi Dong Yu ◽  
Peng Wu ◽  
Yuan Ding ◽  
Feng Gao
Keyword(s):  
Manufacturing Industry ◽  
Evaluation Model ◽  
Global Market ◽  
Rapid Expansion ◽  
Coordination Mechanism ◽  
Case Based Reasoning ◽  
Strategy Formation ◽  
Intelligent Maintenance ◽  
Integration Schemes ◽  
Maintenance Service

Taking on the features of agility, intelligence, Internet and socialization in the wake of rapid expansion of global manufacture and cutthroat competition, to establish an e-intelligence maintenance system is crucial for manufacturing enterprise to reduce costs and increase profits in the global market. Based on the analysis of requirement for e-intelligence maintenance in manufacturing industry of our country, this paper puts forward the remote coordination mechanism, the risk control mechanism and the security mechanism. Then explores the eMS strategy formation and optimization which based on Case-based reasoning, intelligent evaluation model of eMS and an effective integration schemes of realizing an enterprise web e-manufacturing and an e-business tool.

An integrated Lean, Green and Six Sigma strategies

2020 ◽  
Vol 32 (2) ◽  
pp. 201-225 ◽  
Author(s):  
Lokpriya Gaikwad ◽  
Vivek Sunnapwar
Keyword(s):  
Literature Review ◽  
Six Sigma ◽  
Public Perception ◽  
Manufacturing Industry ◽  
Global Market ◽  
Manufacturing Industries ◽  
Future Research ◽  
Content Type ◽  
Integrated Framework ◽  
The Impact

Purpose The purpose of this paper is to present a systematic literature review and its analysis concerning a possible framework, compatibility, drivers and barriers for integrating three manufacturing strategies – Lean, Green and Six Sigma. In particular, analyzing current proposals and identifying the literature gaps in the existing literature from which future research directions and challenges have been suggested for developing a specific integrated framework for the Indian manufacturing industry. Design/methodology/approach This study explores manufacturing strategic area in depth through literature review, which will point out to the better understanding of the compatibility and impact of these initiatives through the conceptual framework, on the performance of the manufacturing organization. Findings The review of shortlisted articles indicates that Lean, Green and Six Sigma (LGSS) strategies help the manufacturing organizations to compete in global markets through the impact of a sustainability strategy for their business. Various researchers provide evidence of challenges like cost reduction, quality improvement, on-time delivery, changing needs of the customers and scarce resources that can be overcome through these strategies to achieve overall business objectives. Research limitations/implications In this research, only works of literature related to LGSS and sustainability have been studied so information related to linking between these strategies in manufacturing industries is limited. Practical implications Help the manufacturing practitioners to deploy three strategies simultaneously in an environment when the linking among LGSS methods in manufacturing industries has not been established. Hence simultaneous deployment of these three strategies helps the organization to boost its operational and environmental performance. Social implications The strategies, LGSS, will be adopted in the operational management to reduce both waste and pollution which will definitely help to society. It will highlight the need for cost effective and easy to implement solutions as well as brand building, which is one of the top incentives for LGSS, highlighting the importance of public perception of how companies operate. Originality/value An integrated framework of the LGSS will help the Indian manufacturing industries to improve performance and competitiveness in the global market.

scholarly journals Application of Computer Simulation for Productivity Improvement of Welding Unit in a Heater Manufacturing Industry: A Case Study Based on Arena

2018 ◽  
Vol 225 ◽  
pp. 01004 ◽  
Author(s):  
Salman Jameh Abrishami ◽  
Mohammad Zeraatkar ◽  
Rasoul Esrafilian ◽  
Seyyed Amir Vafaei ◽  
Seyed Mojib Zahraee
Keyword(s):  
Computer Simulation ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Management Strategies ◽  
Simulation Models ◽  
Global Market ◽  
Productivity Improvement ◽  
Manufacturing Management ◽  
Manufacturing Line

Firm’s efficiency and competitiveness are two important challenges in today’s global market that have motivated many manufacturing firms to plan novel manufacturing management strategies. Nowadays, simulation models have been used to assess different aspects of manufacturing systems. This paper introduces a welding unit of a manufacturing line of heater production as a case study and the basic application of the ARENA software. The main goal of this paper is increasing the productivity of the production line by using computer simulation. To achieve this goal, three various scenarios are compared and suggested to obtain the better improvement in productivity.

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.

A Preliminary Study on Systems Health Management and the Assessment of Future Research Requirements: A Safety Perspective

2010 ◽  
Author(s):  
Tolga Kurtoglu ◽  
Karen M. Leone ◽  
Carl E. Sandifer ◽  
Mary S. Reveley ◽  
Megan A. Thomas ◽  
...  
Keyword(s):  
Health Management ◽  
Integrated System ◽  
Future Research ◽  
Negative Effects ◽  
Management Tools ◽  
Research Areas ◽  
Aircraft Accident ◽  
The Relationship ◽  
Specific Technology

A health management (HM) system is responsible for information gathering about a system’s health and corresponding decision-making. HM systems are typically used to identify any degradation in performance that may affect safety or successful operations of a system. Effective long term development of successful health management solutions requires an improved understanding of the relationship between potential adverse events that may happen during flight, and validated tools, technologies, and techniques developed for mitigating their negative effects on system safety and functionality. This paper presents a study on the assessment of future requirements for systems health management technologies and related research areas. The gist of the paper is the mapping between systems health management technologies and damage conditions extracted from a study of aircraft accident and incident data. The goal of the study is to identify key research areas in systems health management and to recommend specific technology needs to support the development of integrated system health management tools, technologies, and techniques that will address safety related challenges facing current and future aircraft systems.

scholarly journals Cyber-Physical Systems for Micro-/Nano-assembly Operations: a Survey

2021 ◽  
Author(s):  
Jose A Mulet Alberola ◽  
Irene Fassi
Keyword(s):  
Manufacturing Systems ◽  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Global Market ◽  
Added Value ◽  
Market Force ◽  
Future Research ◽  
New Production ◽  
Physical Systems ◽  
Assembly Operations

Abstract Purpose of Review Latest requirements of the global market force manufacturing systems to a change for a new production paradigm (Industry 4.0). Cyber-Physical Systems (CPS) appear as a solution to be deployed in different manufacturing fields, especially those with high added value and technological complexity, high product variants, and short time to market. In this sense, this paper aims at reviewing the introduction level of CPS technologies in micro/nano-manufacturing and how these technologies could cope with these challenging manufacturing requirements. Recent Findings The introduction of CPS is still in its infancy on many industrial applications, but it actually demonstrates its potential to support future manufacturing paradigm. However, only few research works in micro/nano-manufacturing considered CPS frameworks, since the concept barely appeared a decade ago. Summary Some contributions have revealed the potential of CPS technologies to improve manufacturing performance which may be scaled to the micro/nano-manufacturing. IoT-based frameworks with VR/AR technologies allow distributed and collaborative systems, or agent-based architectures with advance algorithm implementations that improve the flexibility and performance of micro-/nano-assembly operations. Future research of CPS in micro-/nano-assembly operations should be followed by more studies of its technical deployment showing its implications under other perspectives, i.e. sustainable, economic, and social point of views, to take full advance of all its features.

scholarly journals Advantages and potential challenges of data management in e-maintenance

2019 ◽  
Vol 25 (3) ◽  
pp. 378-396 ◽  
Author(s):  
Arian Razmi-Farooji ◽  
Hanna Kropsu-Vehkaperä ◽  
Janne Härkönen ◽  
Harri Haapasalo
Keyword(s):  
Data Management ◽  
Design Methodology ◽  
Management Practices ◽  
Future Research ◽  
Conceptual Approach ◽  
Content Type ◽  
Different Types ◽  
Maintenance Systems ◽  
Industry Leader ◽  
Practical Implications

Purpose The purpose of this paper is twofold: first, to understand data management challenges in e-maintenance systems from a holistically viewpoint through summarizing the earlier scattered research in the field, and second, to present a conceptual approach for addressing these challenges in practice. Design/methodology/approach The study is realized as a combination of a literature review and by the means of analyzing the practices on an industry leader in manufacturing and maintenance services. Findings This research provides a general understanding over data management challenges in e-maintenance and summarizes their associated proposed solutions. In addition, this paper lists and exemplifies different types and sources of data which can be collected in e-maintenance, across different organizational levels. Analyzing the data management practices of an e-maintenance industry leader provides a conceptual approach to address identified challenges in practice. Research limitations/implications Since this paper is based on studying the practices of a single company, it might be limited to generalize the results. Future research topics can focus on each of mentioned data management challenges and also validate the applicability of presented model in other companies and industries. Practical implications Understanding the e-maintenance-related challenges helps maintenance managers and other involved stakeholders in e-maintenance systems to better solve the challenges. Originality/value The so-far literature on e-maintenance has been studied with narrow focus to data and data management in e-maintenance appears as one of the less studied topics in the literature. This research paper contributes to e-maintenance by highlighting the deficiencies of the discussion surrounding the perspectives of data management in e-maintenance by studying all common data management challenges and listing different types of data which need to be acquired in e-maintenance systems.

scholarly journals Update on Giardia: Highlights from the seventh International Giardia and Cryptosporidium Conference

Parasite ◽  
2020 ◽  
Vol 27 ◽  
pp. 49 ◽  
Author(s):  
André G. Buret ◽  
Simone M. Cacciò ◽  
Loïc Favennec ◽  
Staffan Svärd
Keyword(s):  
Cell Biology ◽  
Health Management ◽  
Giardia Duodenalis ◽  
Basic Research ◽  
Basic Knowledge ◽  
Future Research ◽  
World Knowledge ◽  
Main Research ◽  
Research Perspectives ◽  
New Findings

Although Giardia duodenalis is recognized as one of the leading causes of parasitic human diarrhea in the world, knowledge of the mechanisms of infection is limited, as the pathophysiological consequences of infection remain incompletely elucidated. Similarly, the reason for and consequences of the very specific genome-organization in this parasite with 2 active nuclei is only partially known. Consistent with its tradition, the 7th International Giardia and Cryptosporidium Conference (IGCC 2019) was held from June 23 to 26, 2019, at the Faculty of Medicine and Pharmacy of the University of Rouen-Normandie, France, to discuss current research perspectives in the field. This renowned event brought together an international delegation of researchers to present and debate recent advances and identify the main research themes and knowledge gaps. The program for this interdisciplinary conference included all aspects of host-parasite relationships, from basic research to applications in human and veterinary medicine, as well as the environmental issues raised by water-borne parasites and their epidemiological consequences. With regard to Giardia and giardiasis, the main areas of research for which new findings and the most impressive communications were presented and discussed included: parasite ecology and epidemiology of giardiasis, Giardia-host interactions, and cell biology of Giardia, genomes and genomic evolution. The high-quality presentations discussed at the Conference noted breakthroughs and identified new opportunities that will inspire researchers and funding agencies to stimulate future research in a “one health” approach to improve basic knowledge and clinical and public health management of zoonotic giardiasis.

Evaluation of Lean Manufacturing Systems Using MADM and Fuzzy TOPSIS

2014 ◽  
Vol 592-594 ◽  
pp. 2628-2638 ◽  
Author(s):  
T.G. Arul ◽  
C. Arumugam ◽  
P. Parthiban
Keyword(s):  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Value Added ◽  
Fuzzy Topsis ◽  
Global Market ◽  
Triangular Fuzzy Numbers ◽  
Management Philosophy ◽  
Order Preference ◽  
Indian Industries ◽  
Real World Situation

Lean manufacturing is a management philosophy derived from Toyota Production System (TPS) which aims to increase the overall values of the product or service provided to the customer through elimination of non-value added activities. In the era of globalisation, to remain competitive in the global market, many medium and small sized Indian industries adopt lean manufacturing. This paper focuses on implementation of lean manufacturing in Indian MSMEs. To examine the implementation, attributes which influence lean manufacturing are obtained and industries’ performances on these criteria are rated. In this paper, the methodology selected from many of the multi criteria models is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In the actual real world situation, because of the unreliable nature of the information gathered, the attributes are often not absolute and are imprecise. These data can be considered as fuzzy and the aim of this paper is to adopt TOPSIS decision making method to problems with fuzzy data. The rating and weights of each data are expressed as triangular fuzzy numbers. These attributes are then normalized and the TOPSIS methodology is carried out to determine the effect of implementing lean manufacturing technique in an industry. The best industry is identified by fuzzy TOPSIS on the basis of performance towards the considered attributes is consistent with results identified by TOPSIS.

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