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1 – 10 of over 48000Jasper Veldman, Warse Klingenberg and Hans Wortmann
Condition‐based maintenance is the diagnosis of component failure or a prognosis of a component's time to failure. The aim of this paper is twofold: a summary of the main…
Abstract
Purpose
Condition‐based maintenance is the diagnosis of component failure or a prognosis of a component's time to failure. The aim of this paper is twofold: a summary of the main assumptions regarding condition‐based maintenance found in the literature into eight postulates, and a comparison of the postulates against industrial practice. The postulates were formulated regarding the technical system, the managerial system and workforce knowledge.
Design/methodology/approach
The postulates were examined in a multiple case study of five large firms in the process industry.
Findings
The results indicate that some postulates were supported with empirical findings. Limited or no support was found for postulates concerning the application of prognostic activities, use of dedicated software, use of procedures, use of training, and the active management of domain‐related knowledge availability.
Practical implications
Practitioners can use the eight postulates as key elements in the management of condition‐based maintenance technology, and for the comparison of their current condition‐based maintenance practices with what literature generally proposes.
Originality/value
Other researchers have reported on condition‐based maintenance, but most publications focus on applied mathematics and new monitoring and simulation models. Only limited attention was paid to industrial practice so far. The study is one of the first in‐depth empirical studies into actual condition‐based maintenance practice.
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The great need for an optimum preventive maintenance strategy coupled with the fast‐developing condition‐monitoring techniques has given rise to the invention of relevant condition…
Abstract
The great need for an optimum preventive maintenance strategy coupled with the fast‐developing condition‐monitoring techniques has given rise to the invention of relevant condition predictor (RCP)‐based maintenance approach. The main purpose of this approach is to prevent the failures due to gradual deterioration of mechanical items in order to improve system reliability and availability. This is done by monitoring relevant condition predictors of constituent maintenance significant items of the system, taking into account the availability and cost‐effectiveness of the monitoring techniques. A comprehensive review of all constituent items is carried out and a systematic approach is used to decide an optimum maintenance policy for each corresponding group of items. An optimum time to the examination of relevant condition predictors is derived mathematically with required reliability as the optimisation criterion in order to implement the RCP‐based maintenance activities.
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Chia Tai Angus Lai, Wei Jiang and Paul R. Jackson
The purpose of this paper is to demonstrate how Internet of Things (IoT) technology can enable highly distributed elevator equipment servicing by using remote-monitoring…
Abstract
Purpose
The purpose of this paper is to demonstrate how Internet of Things (IoT) technology can enable highly distributed elevator equipment servicing by using remote-monitoring technology to facilitate a shift from traditional corrective maintenance (CM) and time-based maintenance (TBM) to more predictive, condition-based maintenance (CBM) in order to achieve various benefits.
Design/methodology/approach
Literature review indicates that CBM has advantages over conventional CM and TBM from a theoretical perspective, but it depends on continuous monitoring enhancement via advanced IoT technology. An in-depth case study was carried out to provide practical evidence that IoT enables elevator firms to achieve CBM.
Findings
From a theoretical perspective, the CBM of elevators makes business sense. The challenges lie in data collection, data analysis and decision making in real-world business contexts. The main findings of this study suggest that CBM can be commercialized via IoT in the case of elevators and would improve the safety and reliability of equipment. It would, thus, make sense from technological, process and economic perspectives.
Practical implications
Our longitudinal real-world case study demonstrates a practical way of making the CBM of elevators widespread. Integrating IoT and other advanced technology would improve the safety and reliability of elevator equipment, prolong its useful life, minimize inconvenience and business interruptions due to equipment downtime and reduce or eliminate major repairs, thus greatly reducing maintenance costs.
Originality/value
The main contribution of this paper lies in the empirical demonstration of the benefits and challenges of CBM via IoT relative to conventional CM and TBM in the case of elevators. The authors believe that this study is timely and will be valuable to firms working on similar research or commercialization strategies.
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Tiedo Tinga, Flip Wubben, Wieger Tiddens, Hans Wortmann and Gerard Gaalman
For many decades, it has been recognized that maintenance activities should be adapted to the specific usage of a system. For that reason, many advanced policies have been…
Abstract
Purpose
For many decades, it has been recognized that maintenance activities should be adapted to the specific usage of a system. For that reason, many advanced policies have been developed, such as condition-based and load-based maintenance policies. However, these policies require advanced monitoring techniques and rather detailed understanding of the failure behavior, which requires the support of an OEM or expert, prohibiting application by an operator in many cases. The present work proposes a maintenance policy that relieves the high (technical) demands set by these existing policies and provides a more accurate specification of the required (dynamic) maintenance interval than traditional usage-based maintenance.
Design/methodology/approach
The methodology followed starts with a review and critical assessment of existing maintenance policies, which are classified according to six different aspects. Based on the need for a technically less demanding policy that appears from this comparison, a new policy is developed. The consecutive steps required for this functional usage profiles based maintenance policy are then critically discussed: usage profile definition, monitoring, profile severity quantification and the possible extension to the fleet level. After the description of the proposed policy, it is demonstrated in three case studies on real systems.
Findings
A maintenance policy based on a simple usage registration procedure appears to be feasible, which enables a significantly more efficient maintenance process than the traditional usage-based policies. This is demonstrated by the policy proposed here.
Practical implications
The proposed maintenance policy based on functional usage profiles offers the operators of fleets of systems the opportunity to increase the efficiency and effectiveness of their maintenance process, without the need for a high investment in advanced monitoring systems and in experts interpreting the results.
Originality/value
The original contribution of this work is the explicit definition of a new maintenance policy, which combines the benefits of considering the effects of usage or environment severity with a limited investment in monitoring technology.
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Mahantesh Nadakatti, A. Ramachandra and A.N. Santosh Kumar
The purpose of this paper is to explain the development and testing of a condition‐monitoring sub‐module of an integrated plant maintenance management application based on…
Abstract
Purpose
The purpose of this paper is to explain the development and testing of a condition‐monitoring sub‐module of an integrated plant maintenance management application based on artificial intelligence (AI) techniques, mainly knowledge‐based systems, having several modules, sub‐modules and sections.
Design/methodology/approach
The approach is applicable to general purpose machinery. A maintenance knowledge base is developed from published information on maintenance management like handbooks, journals, conference proceedings, because of difficulty in accessing expert knowledge and information on actual machine problems, from experts in maintenance management. The knowledge‐based engine comprises intelligent algorithms and software‐generated pop‐ups/alerts/alarms predictive tools. The expert system on an off‐line basis, on a failure in the plant's machinery or deterioration in performance, will trigger fault diagnosis to detect the reason and give immediate advice to the maintenance group.
Findings
Knowledge‐based intelligent machine troubleshooting/maintenance software enables maintenance technicians to refer to custom‐made, ready‐to‐use and easily upgradable maintenance software. Its benefits include: reduction in machine down‐time, reduction in skill level for maintenance activities, ease of maintenance, speedy response and affordable cost. The paper collectively deals with the analysis of the state‐of‐the‐art expert systems for diagnosis and maintenance of general‐purpose industrial machinery.
Research limitations/implications
The software is essentially for general purpose industrial machinery (stand‐alone type) applications. For continuously operating machinery, the software has to be altered to accommodate continuous data through strategically mounted sensors.
Practical implications
Knowledge based, ready‐to‐use, custom‐built, maintenance management software application having many modules and sub‐modules on various aspects of modern maintenance practices has direct application for shopfloor maintenance.
Originality/value
A part of fully‐fledged maintenance management application based on AI principles is discussed in the present paper. Its benefits include: use of latest methodology – AI techniques for maintenance field, ready‐to‐install condition, vast and immediate access to maintenance management information, user‐friendly and interactive modules, easily upgradable features for the application.
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Ashok Prajapati, James Bechtel and Subramaniam Ganesan
The purpose of this paper is to provide a brief overview of condition based maintenance (CBM) with definitions of various terms, overview of some history, recent developments…
Abstract
Purpose
The purpose of this paper is to provide a brief overview of condition based maintenance (CBM) with definitions of various terms, overview of some history, recent developments, applications, and research challenges in the CBM domain.
Design/methodology/approach
The article presents the insight into various maintenance strategies and provides their respective merits and demerits in various aspects. It then provides the detailed discussion of CBM that includes applications of various methodologies and technologies that are being implemented in the field. Finally, it ends with open challenges in implementing condition based maintenance systems.
Findings
This paper surveys research articles and describes how CBM can be used to optimize maintenance strategies and increase the feasibility and practicality of a CBM system.
Practical implications
CBM systems are completely practical to implement and applicable to various domains including automotive, manufacturing, aviation, medical, etc. This paper presents a brief overview of literature on CBM and an insight into CBM as a maintenance strategy. CBM has wide applications in automotive, aviation, manufacturing, defense, and other industries. It involves various disciplines like data mining, artificial intelligence, and statistics to enable the systems to be maintenance intelligent. These disciplines help in predicting the future consequences based on the past and current system conditions. Based on the authors’ studies, implementation of such a system is easy and cost effective because it uses existing subsystems to collect statistical data. On top of that it requires building a software layer to process the data and to implement the prognosis techniques in the form of algorithms.
Social implications
The design of CBM systems highly impact the society in terms of maintenance cost (i.e. reduces the maintenance cost of automobiles, safety by providing real time reporting of the fault using prognosis).
Originality/value
To the best of the authors’ knowledge, this paper is first of its kind in the literature which presents several maintenance strategies and provides a number of possible research directions listed in open research challenges.
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Mike Gerdes, Dieter Scholz and Diego Galar
The purpose of this paper is to analyze the effects of condition-based maintenance based on unscheduled maintenance delays that were caused by ATA chapter 21 (air conditioning)…
Abstract
Purpose
The purpose of this paper is to analyze the effects of condition-based maintenance based on unscheduled maintenance delays that were caused by ATA chapter 21 (air conditioning). The goal is to show the introduction of condition monitoring in aircraft systems.
Design/methodology/approach
The research was done using the Airbus In-Service database to analyze the delay causes, delay length and to check if they are easy to detect via condition monitoring or not. These results were then combined with delay costs.
Findings
Analysis shows that about 80 percent of the maintenance actions that cause departure delays can be prevented when additional sensors are introduced. With already existing sensors it is possible to avoid about 20 percent of the delay causing maintenance actions.
Research limitations/implications
The research is limited on the data of the Airbus in-service database and on ATA chapter 21 (air conditioning).
Practical implications
The research shows that delays can be prevented by using existing sensors in the air conditioning system for condition monitoring. More delays can be prevented by installing new sensors.
Originality/value
The research focuses on the effect of the air conditioning system of an aircraft on the delay effects and the impact of condition monitoring on delays.
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Frank Koenig, Pauline Anne Found and Maneesh Kumar
The purpose of this paper is to present the findings of a recent study conducted with the objective of addressing the problem of failure of baggage carts in the high-speed baggage…
Abstract
Purpose
The purpose of this paper is to present the findings of a recent study conducted with the objective of addressing the problem of failure of baggage carts in the high-speed baggage tunnel at Heathrow Terminal 5 by the development of an innovative condition-based maintenance (CBM) system designed to meet the requirements of 21st century airport systems and Industry 4.0.
Design/methodology/approach
An empirical experimental approach to this action research was taken to install a vibration condition monitoring pilot test in the north tunnel at Terminal 5. Vibration data were collected over a 6-month period and analysed to find the threshold of good quality tyres and those with worn bearings that needed replacement. The results were compared with existing measures to demonstrate that vibration monitoring could be used as a predictive model for CBM.
Findings
The findings demonstrated a clear trend of increasing vibration velocity with age and use of the baggage cart wheels caused by wheel mass unbalanced inertia that was transmitted to the tracks as vibration. As a result, preventative maintenance is essential to ensure the smooth running of airport baggage. This research demonstrates that a healthy wheel produces vibration of under 60 mm/s whereas a damaged wheel measures up to 100 mm/s peak to peak velocity and this can be used in real-time condition monitoring to prevent baggage cart failure. It can also run as an autonomous system linked to AI and Industry 4.0 airport logic.
Originality/value
Whilst vibration monitoring has been used to measure movement in static structures such as bridges and used in rotating machinery such as railway wheels (Tondon and Choudhury, 1999); this is unique as it is the first time it has been applied on a stationary structure (tracks) carrying high-speed rotating machinery (baggage cart wheels). This technique has been patented and proven in the pilot study and is in the process of being rolled out to all Heathrow terminal connection tunnels. It has implications for all other airports worldwide and, with new economic sensors, to other applications that rely on moving conveyor belts.
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Zhigang Tian and Han Wang
Wind power is an important source of renewable energy and accounts for significant portions in supplying electricity in many countries and locations. The purpose of this paper is…
Abstract
Purpose
Wind power is an important source of renewable energy and accounts for significant portions in supplying electricity in many countries and locations. The purpose of this paper is to develop a method for wind power system reliability assessment and condition-based maintenance (CBM) optimization considering both turbine and wind uncertainty. Existing studies on wind power system reliability mostly considered wind uncertainty only and did not account for turbine condition prediction.
Design/methodology/approach
Wind power system reliability can be defined as the probability that the generated power meets the demand, which is affected by both wind uncertainty and wind turbine failures. In this paper, a method is developed for wind power system reliability modeling considering wind uncertainty, as well as wind turbine condition through health condition prediction. All wind turbine components are considered. Optimization is performed for maximizing availability or minimizing cost. Optimization is also conducted for minor repair activities to find the optimal number of joint repairs.
Findings
The wind turbine condition uncertainty and its prediction are important for wind power system reliability assessment, as well as wind speed uncertainty. Optimal CBM policies can be achieved for optimizing turbine availability or maintenance cost. Optimal preventive maintenance policies can also be achieved for scheduling minor repair activities.
Originality/value
This paper considers uncertainty in both wind speed and turbine conditions and incorporates turbine condition prediction in reliability analysis and CBM optimization. Optimization for minor repair activities is studied to find the optimal number of joint repairs, which was not investigated before. All wind turbine components are considered, and data from the field as well as reported studies are used.
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Lawrence Mann, Anuj Saxena and Gerald M. Knapp
The focus of preventive maintenance (PM) programmes in industry isshifting from a pure statistical basis to online condition monitoring.Examines the shortcomings of statistical…
Abstract
The focus of preventive maintenance (PM) programmes in industry is shifting from a pure statistical basis to online condition monitoring. Examines the shortcomings of statistical‐based PM which are contributing to this shift, and the potential benefits of and current research issues within condition‐based PM. Notes that statistics and quality control techniques will continue to play a critical role in this evolution.
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