Customers´ Voice: Predictive Maintenance in Manufacturing, Western Europe

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Customers´ Voice: Predictive Maintenance in Manufacturing, Western Europe

  • Consolidated insights of more than 300 interviews with industry experts in Western Europe (in total over 250 hours of interviews)
  • Over 50 slides (16:9) for direct presentation but with deep explanations (hybrid format) – see examples in preview
  • Content covers status quo of maintenance and IT technology adaption as well as customer needs in regard to Predictive Maintenance solutions
  • The report is suited specially for Marketing and Sales in IT companies as well as Production and IT in Manufacturing companies
  • Results are prepared in English – each license contains half an hour of exchange with our analysts
  • Free excerpt – find it here
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Description

The infusion of IoT into the world of asset-intensive industries has enabled companies to benefit from revolutionary use cases such as Predictive Maintenance. It is fast growing in stature and already has a strong market potential for the next years. The study is aimed at better understanding the Predictive Maintenance market from the users’ point of view by gathering awareness with respect to its current state and future adoption potential.

The focus is to generate insights about the adoption of Predictive Maintenance solutions based on interconnected concepts like current presence along the implementation funnel, expectations from technology providers, technical infrastructure maturity and pain points with regard to Predictive Maintenance.

To create this study, a panel of around 300 experts in different asset-intensive domains (example: Aerospace & Defence, Automotive, Electrical, Mechanical, Energy and Utilities) were interviewed. The geographic scope for this study was focused on 15+ industrialized nations across Europe. The respondents represented a diverse range of small, medium and large companies with a third of the companies having a revenue of over USD 1 billion. 80% of the respondents work in key decision-making positions in production, maintenance, logistics or quality departments.

Following the detailed agenda of your report:

  • Familiarity with concept of Pred. Maintenance
  • Predictive Maintenance – a hype topic?
  • Opinions and Predictions
  • Components of a Predictive Maintenance System
  • Excursus: Predictive Analytics in Predictive Maintenance
  • Evolution of Predictive Maintenance concepts
  • Status quo Maintenance technologies
  • IT Solutions: Definition/ Explanation
  • Status Quo IT solution usage
  • Big Data Analytics usage prior to Pred. Maintenance implementation
  • Main Types of Data Storage Infrastructure
  • Preferred type of data storage infrastructure
  • Current pain points in Manufacturing companies
  • Concrete impact of unplanned shut downs
  • Number of unplanned hours on production line
  • Share maintenance costs on production costs
  • Estimated savings potential due to Predictive Maintenance
  • Responsible party for maintenance/ optimal working for machines & assets
  • Predictive Maintenance funnel phases
  • Key stakeholder involved in process of Predictive Maintenance implementation
  • Time spending per implementation phase
  • Recommendations for smooth implementation
  • What characterizes a good Predictive Maintenance solution
  • Preferred customer touch points
  • Relevant needs to be addressed by Predictive Maintenance solution
  • Relevant decision criteria for provider selection
  • Excurses: Predictive Maintenance Vendor Engagement Models
  • Key barriers and obstacles regarding implementation
  • Main Vendors: Predictive Maintenance
  • Selected partnerships among Predictive Maintenance providers
  • Awareness and capability evaluation of Predictive Maintenance providers
  • Preferred type of providers for solution sourcing

Additional information

License

One user license, Team license, Company License, Test