Smart maintenance management approach: Critical review of present practices and future trends in SMEs 4.0

Velmurugan, K.; Saravanasankar, S.; Sankaranarayanan, Bathrinath

doi:10.1016/j.matpr.2022.02.622

Cited by 12 publications

(8 citation statements)

References 26 publications

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“…Reducing maintenance costs while increasing production performance and assessing several scenarios in the maintenance is described in the publication [14]. An important source of knowledge is also a critical analysis of computer-aided maintenance management systems as in the text [15]. The non-technical sphere brings the interconnection of sustainable, social and economic requirements for technical systems as in the text [16].…”

Section: Methodsmentioning

confidence: 99%

“…Multi-target optimisation algorithm for wind turbine maintenance is used in the publication [14]. The explanation in computer-aided maintenance management when considering aspects of the Industry 4.0, such as neural network, models, clouds, the Internet of Things, the article [15] provides. The study [16] assesses and categorises maintenance services across their life cycle and in relation to the Industry 4.0.…”

Section: Publications and The Maintenance Managementmentioning

confidence: 99%

“…Many organisations have difficulty to implement the conception TPM and a spatial arrangement of equipment in a shopfloor as the article [13] describes. The eternal problem is to reduce maintenance costs and increase equipment availability for many articles as in [15,18]. Problems can be seen in the supply chain in the text [19].…”

Section: Problems Of Areamentioning

confidence: 99%

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The Maintenance Management

Pelantová¹

2023

Maintenance Management - Current Challenges, New Developments, and Future Directions

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The chapter deals with the maintenance management. The review is based on maintenance and management trends in organisations in 2022 and on other findings. There are also historical parallels. Aspects such as maintenance planning and control and management including downtime, resources in terms as material (spare parts and added materials) and personnel are discussed. The issue is linked to other management systems such as quality control, occupational safety, and environment and information security. The methods of planning and control of equipment maintenance are presented. The application of the process approach and the concept of maintenance as a process that needs to be improved are described. The relationship to the Industry 4.0 is mentioned. Linking to risk management is included in this chapter. The chapter is based on a small survey probe in several organisations, and points out identified nonconformities of the maintenance and suggested actions. The goal is effective maintenance for needs of organisations in a current dynamic environment.

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Section: Methodsmentioning

confidence: 99%

Section: Publications and The Maintenance Managementmentioning

confidence: 99%

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The Maintenance Management

Pelantová¹

2023

Maintenance Management - Current Challenges, New Developments, and Future Directions

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“…e detailed overview of the smart maintenance management system and the factor analysis of the implementation of the smart maintenance managements has been explained. e human error factors are evaluated for developing the best maintenance scheduling and planning in the industry [33,34]. rough this systematic literature review process, recent research in the field of smart maintenance and management has been dealt with and predicted the future scope, challenges, and the research gap of this real-time industrial case study research study also be elaborated on in the next section.…”

Section: Review Of Literaturementioning

confidence: 99%

Availability Analysis of the Critical Production System in SMEs Using the Markov Decision Model

Velmurugan

Saravanasankar

Venkumar³

et al. 2022

Mathematical Problems in Engineering

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Small and medium-sized enterprises (SMEs) in today’s world have numerous issues in ensuring the availability and safety of critical machines and their components in the working environment. As a result, SMEs considered planning and scheduling maintenance tasks to be a significant threat. The goal of this research is to identify the critical subsystem of the automobile spare parts production plant in the southern region of Tamil Nadu, India, and then to prioritize the maintenance activity and set up an architecture for autonomous preventive maintenance (PM) in SMEs that includes an optimal decision support system. The transition state diagram of the individual and simultaneous production system has been developed with the application of the Markov decision model approach. It was used to analyze the present variables of the production systems and forecast the optimal maintenance parameters such as the failure rate and the repair rate, through the production system’s availability analysis. This availability analysis reveals that system B (Piercing) is classified as the most critical because of the abrupt availability variation compared to all other production systems, concerning the corresponding maintenance parameters such as a failure rate of 0.0371, a repair rate of 0.7094, and the availability of the piercing system of 0.5056. Finally, the use of an autonomous PM management system and the most effective maintenance workforce has enhanced productivity and customer satisfaction in SMEs. The predictive maintenance management system has been further investigated to determine the real-time remaining useful life (RUL) of critical systems in the automobile spare parts manufacturing plant in the southern region of Tamil Nadu, India.

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“…Vibration monitoring of damage assessment of RC building life validity through a retro filled RC frame model was also explained in a real time case study of a construction project [22]. A critical overview of a smart maintenance management system and factor analysis of the implementation of a digital and optimal maintenance management system were illustrated [23,24]. Through this analysis, optimal maintenance management activities were initiated.…”

Section: Introductionmentioning

confidence: 99%

IIoT Based Anomaly Detection and Maintenance Management of an Industrial Rotary System

Velmurugan

Saravanasankar

Venkumar³

et al. 2022

Curr. Appl. Sci. Technol.

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Numerous challenges are being faced by implementing the Industrial Internet of Things (IIoT), which enables anomaly detection and optimal maintenance management of industrial production systems and their critical machines. Industries have started adopting this revolutionary technology along with other allied technologies to reap the full benefits out of Industry 4.0 environment. The objectives of this research work were to use the IIoT to develop a continuous monitoring system of the behavior of bottleneck facilities in a production system, to predict and avoid all possible failures, and to improve the overall productivity of the manufacturing system. The proposed prognostic health monitoring system employs IIoT sensors to measure the current values of the operating parameters of a machine, using built-in intelligent decision support mechanism to compare with optimal ranges of values, and to message the appropriate alarming signals as per the severity of the deviation. The system developed was tested with a prototype model comprising the Internet of Things, internet communication technology, and a machine learning algorithm, MEMS with standard input, output, storage and display of components, which was developed in a laboratory but implemented in a case study in a real industrial production plant. After the successful implementation of the developed system, the performance of the critical machine was evaluated in terms of metrics such as the average number of failures, average downtime and average service time spent. It was found that after the implementation, the downtime has decreased by nearly 22% and for the performance in terms of its output, the flow rate exhibited a steady increase with the passage of time.

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Smart maintenance management approach: Critical review of present practices and future trends in SMEs 4.0

Cited by 12 publications

References 26 publications

The Maintenance Management

The Maintenance Management

Availability Analysis of the Critical Production System in SMEs Using the Markov Decision Model

IIoT Based Anomaly Detection and Maintenance Management of an Industrial Rotary System

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