Predictive maintenance provider nucleus itself on speculating issues before they actually occur. Predictive maintenance provider definition verifies the availability of machines and minimizing its resource consumption consulting for repairs whilst keeping an eye on the quality of the product on the production helped by the employees. It is also known as condition-based monitoring because the maintenance is done when it is needed not when something fails or a schedule which does not applies to the need of the product. The explanation of productive maintenance provider is based on traditional condition monitoring amplifying and consulting companies business with technological/ digital advances program, thus predicting the failure beforehand. Therefore, it involves

  • Collection of data
  • Evaluation of data
  • Optimizing and predicting Maintenance process.

Predictive maintenance provider focuses on data analytics, to see patterns and make reasonably accurate prediction of Application examples in companies business as to when a piece of product needs to be repaired or replaced. Predictive maintenance provides the promise to optimize maintenance tasks in real time in machine learning, maximizing the useful life of their equipment in production while still avoiding disruption to operation programm.

Essential component of a predictive maintenance strategy

  • Explanation and Research of the problem
  • Understanding the current consulting operational level programm
  • Understanding the technology required for predictive maintenance including the technological advancements, internet of things, sensors, software’s (for example cloud), infrastructure needs, industry 4.0, machine learning, etc
  • Creating and implementation strategy in production
  • Designing and running pre-tests and looking for Application examples such as Microsoft office 365 businesses. (for example, companies with business in Germany designs and runs pre-test with the help of employees to look for examples in productive maintenance provider)
  • Planning for the required change

However, only strategy is not enough. Operating the developmental model into an operation involves provisioning infrastructure, installing and configuring software (for example, cloud), preparing data, and testing both code and data. For example, we can use window 365 on the Microsoft Office 365 Business app digitally on mobile or desktop as a service/DaaS. IFPM Institute in germany with the help of employees uses windows cloud in their home office.

There are several firms that have worked on Predictive Maintenance programm implementations stemming from different segments. These are as follows:

  • Condition Monitoring Hardware
  • Industrial Automation Hardware
  • Connectivity
  • Storage & Platform
  • Analytics

 The top 5 companies that use predictive maintenance anbieter:

  1. IBM
  2. SAP
  3. Siemens
  4. Microsoft
  5. GE

Preventive maintenance vs predictive maintenance

Definition of Preventive maintenance is that it is a work that are regularly scheduled based on time, asset runtime, or some other period of time, etc in machine learningDefinition of Predictive maintenance is that it is a work that is scheduled based on need of the company or on real time condition of the asset in machine learning (for example Microsoft office 365 business in cloud used in Germany), etc.


The similarity between preventive Maintenace and predictive maintenance provider is that:

  • Preventive maintenance and predictive maintenance are designed to increase the reliability of the assets and decrease the amount of reactivity to failures.
  • They are both also known as scheduled maintenance because their work orders are scheduled in advance of the actual term.


The difference between predictive maintenance and preventive maintenance is that:

  • The preventive maintenance is regularly scheduled at regular intervals in companies business while predictive maintenance is done based on asset condition or as needed.
  • The preventive maintenance is cost comparatively less in companies business with cloud while the predictive maintenance reduces the cost of labor and material in companies business.
  • The trigger of preventive maintenance is time whereas the predictive maintenance is condition.
  • The cost savings of preventive maintenance is low whereas the cost savings of predictive maintenace is either medium or high.
  • The resource needed for preventive maintenance is maintenance is maintenance software for scheduling, maintenance scheduler, and preventive maintenance checklists. The resource needed for predictive maintenance is maintenance software for scheduling, maintenance scheduler, condition monitoring software, condition tools, sensors, internet of things, sensors, software’s, infrastructure needs, industry 4.0, etc.
  • Pros for preventive maintenace is that it is comparatively very east to implement and better than reactive maintenance whereas the pros for predictive maintenance is that it is performed when needed and reduced the downtime of Application examples.
  • The cons for preventive maintenance is that it has risk of over-maintaining and is very labor intensive whereas the cons for predictive maintenance is that it requires expensive technology and intensive time to implement it correctly.