Our Predictive Maintenance solution is built upon five layers of analysis.

  1. Define vision and achievable goals
  2. Identify data sources and select relevant inputs
  3. Perform an off-line analysis and prove the feasibility
  4. Rapidly implement a small-scale solution and prove the benefit
  5. Integrate the solution in its full context

At ERNI, we start by creating a model and prediction based on our workstation and show it to you as a proof of concept. We also show you detailed visualisations based on the analysis of the tools.
Once we identify something that works, predictions become inputs that can automate the flow by modelling a good predictor. We deploy it as a web service in order to automatically collect the data and also model some actions based on the model of prediction. It is best to have all these tools gathered in just one toolbox. For example, the Microsoft platform is very powerful, but you can also use any other Cloud provider like Google, Amazon or IBM.

Technology trends are paving the way for a Predictive Maintenance revolution

The science of maintenance is on the cusp of a brand new transformation. The advancements in AI technology combined with Cloud solutions are disrupting the industry the way Predictive Maintenance once did; making room for an easy-to-deploy Predictive Maintenance solution. This new trend is known as the Industrial Internet of Things (IIoT).

The Industrial Internet of Things can collect an impressive amount of data from manufacturing equipment in production and transmit it to devices that can store and analyse it. The main obstacle when trying to implement the technology used to be analysing the data that had been collected. By using an Edge Computing-Servers, this analysis can easily be done on site and in real time. This greatly diminishes the burden on networks and also keeps the costs low. An Aberdeen Group study found that the best-in-class organisations (top 20 per cent) that employ predictive analytics for asset management attained:

  • Increase in return on assets (ROA) of up to 24%
  • Reduced unscheduled downtime to 3.5%
  • Improve overall equipment effectiveness to 89%
  • Cost reduction of maintenance of 13%.

News from ERNI

In our newsroom, you find all our articles, blogs and series entries in one place.

  • 06.12.2023.

    Streamlining software development: The journey from multiple to unified requirements management tools

    Productivity in software development is slowed down by managing specifications across various requirements management (RM) tools. Although moving to a single, updated RM tool involves an upfront investment, the long-term benefits are considerable. These include increased process efficiency, enhanced collaboration, superior traceability, improved software specification quality, cost reductions, scalability and better integration with other RM tools, among others.

  • 22.11.2023.

    Recognising trends: An insight into regression analysis

    Data plays a very important role in every area of a company. When it comes to data, a distinction is made primarily between operational data and dispositive data. Operational data play an important role, especially in day-to-day business. However, they are not nearly as relevant as dispositive data. This is because these data are collected over a longer period of time and provide an initial insight into the history or the past.

  • 08.11.2023.

    Why do we need digital transformation for medical devices?

    For hospitals, it is not up for discussion as to whether they want to digitalise. The increasing age of the population in western countries and the progressive shortage of medical professionals mean that without digitalisation, the healthcare system will not be able to provide the quality that patients want in the future.

  • 25.10.2023.

    Mastering the challenges of mobile app testing: Strategies for efficient quality assurance

    Discover the unique challenges faced in testing mobile applications and learn how to overcome them effectively. From selecting suitable devices and operating systems to leveraging cloud-based test platforms, test automation and emulators, this article provides seven essential strategies for optimising your mobile app testing process.

  • 11.10.2023.

    Incorporating classical requirements engineering methods in agile software development for a laboratory automation system

    Traditional agile methodologies can sometimes struggle to accommodate the complexity and regulatory requirements of laboratory automation systems, leading to misalignment with stakeholder needs, scope creep, and potential delays. The lack of comprehensive requirements documentation can result in ambiguous expectations and hinder effective communication among cross-functional teams.

  • 27.09.2023.

    Unveiling the power of data: Part III – Navigating challenges and harnessing insights in data-driven projects

    Transforming an idea into a successful machine learning (ML)-based product involves navigating various challenges. In this final part of our series, we delve into two crucial aspects: ensuring 24/7 operation of the product and prioritising user experience (UX).

  • 13.09.2023.

    Exploring Language Models: An overview of LLMs and their practical implementation

    Generative AI models have recently amazed with unprecedented outputs, such as hyper-realistic images, diverse music, coherent texts, and synthetic videos, sparking excitement. Despite this progress, addressing ethical and societal concerns is crucial for responsible and beneficial utilization, guarding against issues like misinformation and manipulation in this AI-powered creative era.

  • 01.09.2023.

    Peter Zuber becomes the new Managing Director of ERNI Switzerland

    ERNI is setting an agenda for growth and innovation with the appointment of Peter Zuber as Managing Director of the Swiss business unit. With his previous experience and expertise, he will further expand the positioning of ERNI Switzerland, as a leading consulting firm for software development and digital innovation.