Data Driven Energy Centered Maintenance

The use of new technologies, such as Artificial Intelligence and Machine Learning, in the building maintenance industry to drive digital transformation and enable data-driven decision-making for energy-centered maintenance. The book discusses the latest technologies and their applications in maintenance, including different maintenance types, the centered maintenance model, energy-centered maintenance processes, and measures of equipment and maintenance efficiency. It also highlights the benefits of digitalization, such as reduced equipment failure rates, improved equipment reliability, increased efficiency, and extended equipment lifespan. The book is aimed at building operators and building automation companies.

\n Format: Hardback
\n Length: 244 pages
\n Publication date: 20 July 2021
\n Publisher: River Publishers
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Over the past few years, the building maintenance industry has witnessed the introduction of numerous innovative technologies aimed at driving its digital transformation. The prevailing trend in this digital evolution revolves around the adoption of data-driven decision-making, which presents exciting opportunities for an energy-centered maintenance model. Artificial Intelligence (AI) and Machine Learning (ML) are playing pivotal roles in elevating the maintenance team to a new level of maintenance intelligence, enabling them to provide real-time early warning of abnormal equipment performance.

This edition follows a similar methodology as its predecessor. It offers comprehensive explanations of the latest technologies associated with AI and ML, empowering data-driven decision-making processes related to equipment operation and maintenance. The book delves into various technical topics, including:

Different Maintenance Types and the Need for Energy Centered Maintenance:
Understanding the diverse maintenance types and recognizing the importance of energy-centered maintenance is crucial in optimizing equipment performance and reducing operational costs.

The Centered Maintenance Model:
This model focuses on proactive maintenance strategies that prioritize the preservation of equipment assets and their associated energy consumption. It involves the integration of various maintenance activities, such as inspection, repair, and replacement, into a comprehensive plan.

Energy Centered Maintenance Process:
A detailed explanation of the energy-centered maintenance process, including its key steps, methodologies, and tools. This process helps identify energy-saving opportunities, optimize equipment performance, and reduce overall energy consumption.

Measures of Equipment and Maintenance Efficiency and Effectiveness:
Evaluating the efficiency and effectiveness of equipment and maintenance activities is essential for identifying areas for improvement and maximizing resource utilization. This includes measures such as Asset Performance Management (APM), Reliability Centered Maintenance (RCM), and Total Productive Maintenance (TPM).

Data-Driven Energy Centered Maintenance Model:
This model leverages digital technologies and data analytics to enable energy-centered maintenance tasks. It involves the digitization of maintenance inspections, the use of AI and ML algorithms to analyze equipment data, and the development of predictive maintenance models to identify potential issues before they occur.

Artificial Intelligence and Machine Learning in Energy Centered Maintenance:
A comprehensive exploration of the role of AI and ML in energy-centered maintenance. It covers topics such as machine vision, natural language processing, and predictive analytics, which are used to enhance equipment diagnosis, optimize maintenance schedules, and improve overall equipment reliability.

Model Capabilities and Analytics Rules:
An in-depth discussion of the capabilities and analytics rules of energy-centered maintenance models. It covers topics such as model training, validation, and performance evaluation, as well as the development of customized rules and algorithms to meet specific maintenance requirements.

Building Management System Schematics:
A detailed presentation of building management system schematics, including their components, functionalities, and integration with energy-centered maintenance models. This section provides insights into how building automation systems can be utilized to optimize building operations and maintenance procedures.

The book offers a comprehensive description of the digital transformation process undergone by most maintenance inspection tasks as they transition from manual triggers to automated processes. It is designed to cater to building operators as well as building automation companies that are actively striving to digitalize building operation and maintenance procedures. The primary benefits of adopting an energy-centered maintenance model include:

Reductions in Equipment Failure Rate:
By identifying and addressing potential issues before they escalate into failures, energy-centered maintenance can significantly reduce the equipment failure rate, minimizing downtime and associated costs.

Improvements in Equipment Reliability:
Proactive maintenance and regular inspections help maintain equipment in optimal condition, improving its reliability and reducing the risk of unexpected breakdowns.

Increases in Equipment Efficiency:
Energy-centered maintenance practices focus on optimizing equipment performance, reducing energy consumption, and improving overall efficiency, leading to cost savings and increased profitability.

Extended Equipment Lifespan:
Proper maintenance and timely interventions can extend the equipment lifespan, reducing the need for frequent replacements and minimizing the overall maintenance expenses.

In conclusion, the building maintenance industry is undergoing a remarkable transformation driven by the introduction of innovative technologies, including AI and ML. These technologies empower data-driven decision-making, enabling the adoption of an energy-centered maintenance model. By leveraging the power of AI and ML, the maintenance team can elevate their intelligence, provide real-time early warning of abnormal equipment performance, and optimize equipment operation and maintenance processes. The benefits of this transformation include reduced equipment failure rates, improved equipment reliability, increased equipment efficiency, and extended equipment lifespan. As the industry continues to evolve, it is expected that energy-centered maintenance will become an increasingly important aspect of building operations, driving efficiency, sustainability, and profitability.

\n Weight: 596g\n
Dimension: 160 x 242 x 21 (mm)\n
ISBN-13: 9788770223577\n
Edition number: 2 New edition\n