Preventive maintenance and repair of cranes 

Preventive maintenance is a proactive and periodical servicing of equipment such as cranes that are designed to reduce breakdowns, ensure good condition and proper functionality. The cranes require regular inspection and maintenance to promote safety in job sites. The repair and maintenance procedures are provided by the manufactures and Occupational Safety Health Administration. (OSHA) and other regulatory bodies. Preventive maintenance is recommended to the contractors and property owners to improve the lifespan of cranes while reducing downtime.

Types of preventive maintenance 

Preventive maintenance promotes continuous usage of cranes and prevents any total shutdown of machines to repair. Different organizations have their specific set of maintenance but there are four general types of preventive maintenance that are performed on crane parts and components to minimize risks.

Time-based maintenance 

Time-based maintenance is also known as periodic maintenance and is carried out on cranes at planned periods within a year. It can be scheduled and performed annually, quarterly monthly, and even weekly but the period is accordingly set by the manufacturer’s guidelines, recommendations, and the performance of the cranes over a certain period. Time-based maintenance can include inspecting, cleaning, lubricating, servicing, replacement of parts among other activities.

Usage-based maintenance 

Usage-based maintenance aims to maximize the service period of a crane by inspecting the condition and carrying out the necessary repairs. Additionally, it is conducted on the estimated utilization. For instance, if a construction site uses a crane every day, it is essential to monitor and track the operating hours and then do the maintenance. This maintenance can be anything like changing the oil or worn-out parts and ensuring the machine remains in good working condition.

Predictive maintenance 

The predictive maintenance is centered on monitoring the performance and the condition of the cranes to predict the likely time in which a breakdown might occur and address the fault before it happens. This type of maintenance focuses on preventing any possible failures on the cranes. Today, most cranes are designed with sensors that help in gathering a range of data through the internet of things. When such data is collected, it is analysed to draw reliable insights that are used to determine the parts that could fail. The next thing is the repair of all the parts that are likely to break down. 

Prescriptive maintenance 

Prescriptive maintenance is closely related to predictive maintenance because it includes making decisions based on collected data. But this type of maintenance involves advanced use of software tools and algorithms that are meant to evaluate the condition of cranes among other equipment and provide recommendations regarding the repair. This smart technology requires high computerization of machines, automation, and the internet of things.

Predictive maintenance can be very helpful where an organization has created a comprehensive checklist that meets all the intended goals. However, a good checklist also considers the original manufacturers’ guidelines and the history of the equipment. For example, if some parts of the crane have experienced regular breakdowns, it is important to take such conditions into account and minimize any reactive maintenance costs that could be expensive.

Every organization that sells or rents cranes can help their clients in designing a better maintenance program that suits your business. One of the leading market leaders in cranes is and they have been working with different sizes of organizations in providing tailored solutions across the globe to enable them to improve efficiency and increase cranes life expectancy. They are specialists in different types of cranes including all-terrain cranes, heavy-duty crawler cranes, harbor crane rough terrain cranes, self-erecting tower cranes, mini cranes, all-terrain lattice boom cranes among other models.

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