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Digital Technologies Industry 4.0 – Maintenance & Repair


What was the purpose of digitalization of production? In order to avoid the human factor, reduce the number of errors in decision-making due to human fault. And decisions in the modern world for managing complex production assets need to be made a lot, and decisions should be based on a large amount of data and their analysis.

In accordance with ISO 55000, the goal of asset management is to balance the costs, productivity and risks associated with assets.

Agree that it is impossible to solve these tasks that the standard for asset management sets before us without digitalization. And this is not only about the introduction of ACS MRO.

Let’s see what modern digital technologies are and how they can help improve the efficiency of asset management in general, and increase the efficiency of MRO in particular?

As a basis, we took 7 technologies of Industry 4.0, described by Klaus Schwab, President of the World Economic Forum in Davos, in his book “Technologies of the Fourth Industrial Revolution”:

  • IoT Industrial Platforms (Internet of Things)
  • Big data and analytics (Big Data)
  • Cloud computing
  • Additive manufacturing
  • Augmented Reality
  • Digital doubles
  • Machine learning
  • Probably, such integration of MRO and digital technologies looks fantastic, but in reality – these are real tasks that can already be implemented in your production today thanks to existing technologies. The future has already come, it remains only to take a step towards him.

Selecting priority equipment by modeling the consequences and likelihood of failure and developing service strategies and tactics for it

Technology: IoT, Big Data, Cloud Computing, Machine Learning, Digital Twins

  • Data is collected on the condition of the equipment and its performance.
  • The base can be connected to all existing equipment, not only at a specific enterprise.
  • The conditions of the enterprise and equipment context are added to the equipment status data.
  • The methods used are FMEA, FTA, RCM. The situations of potential non-achievement of asset goals and potential risks are simulated.

Development of equipment maintenance plan taking into account the required parameters of reliability, performance and budget availability

Technology: Big Data, IoT, Cloud Computing, Machine Learning, Digital Twins

  • Integrates data from MES, SCADA, HR, etc.
  • Input data: equipment passports, working conditions, spare parts database, storage capabilities, integration with suppliers of spare parts, equipment, contractors, staff competencies, financial forecasts, asset acquisition goals, production planning.
  • Failure development is simulated for certain periods of service and load. When calculating models, data on equipment connected to the global network are used.
  • An assessment of the feasibility of equipment modernization is made.

Setting tasks for maintenance and repair performed both when equipment for repair is stopped and during its operation, taking into account technological installations

Technology: Big Data, IoT, Cloud Computing, Digital Doubles, AR / VR, Additive Manufacturing, Digital Competencies

  • Finding the optimal balance in coordinating production and the necessary service operations is decided by modeling the situation on the basis of: 1. data on the condition of the equipment; 2. the availability of additive and standard materials and spare parts; 3. production and service capabilities.
  • Order orders (tasks for the performance of work) are formed in the form of instructions with support in augmented reality for performers who have passed the assessment and verification of competencies based on their behavior models.

Maintenance and repair work and database replenishment

Technology: Big Data, IoT, Digital Doubles, AR / VR, Additive Manufacturing

  • 3D printing of spare parts.
  • Input quality check of spare parts, recording their parameters in the cloud for analysis and forecasting of a resource.
  • Creation of virtual instructions for working with equipment failures, including data collection for root cause analysis and modeling of failure prevention options.
  • Immediate adjustment of the processes of repair, shutdown, start-up time, necessary additional resources, etc. in the process of servicing in case of discrepancies between the drawn up plan and the achieved current result.
  • The use of VR / AR for remote consulting on service operations in the absence of a competent contractor.

Review parameters for process optimization

Technology: Big Data, Cloud Computing, Digital Twins

  • Due to the use of the capabilities of Industry 4.0 technologies, a cycle of improvements and analysis is built into each stage of asset management, respectively, a separate business process for analysis and improvement is no longer needed.

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