Integrated Prescriptive Maintenance System (PREMSYS) for Construction Equipment Based on Productivity

Abstract

Abstract It is now imperative to create smart systems that prevent mechanical damage through timely preventive maintenance, particularly in construction projects with strict time schedules and budgets. Construction equipment is the largest capital investment for construction companies. Proper maintenance is of major importance for efficiency, productivity, minimization of equipment costs, and environmental management. The aim of this study is to propose an integrated smart system that will monitor the condition based on productivity of the equipment and will provide diagnostic data, helping to optimize the production process, achieve timely maintenance and increasing the expected “economic” life of the equipment. At the same time, it will positively provide the concept for sustainable or green construction with the minimization and elimination of harmful effects on the environment and on the human. The system will include sensors, placed on specific construction equipment components, and will collect measurements for their use and condition, through real-time data export. These data will then be sent using wireless networks to a main server. Extraction of performance measurements and machine learning (ML) data processing will determine when the equipment needs predictive maintenance and repair. Proper, timely and prescriptive maintenance of construction equipment will reduce their environmental footprint and any human harmful emissions, while saving energy during their operating phase and optimizing production processes through monitoring “dead” time.