SENSEYE PDM’S PRODUCT DESIGN. ADAPTABILITY TO CLIENT REQUIREMENTS

Easy Engineering: Tell us about your company’s range of products/solutions.

SENSEYE: While Senseye PdM is a multi-tenanted, cloud-based application, it treats every machine connected to it as unique.

Each machine has its rich history of behavior, maintenance, and use, and each user has their tastes and preferences for what they consider interesting (or not). Senseye PdM uses AI to automatically understand machines and their maintainers to predict upcoming issues with machinery so that failures can be avoided and the correct maintenance actions performed when needed.

Senseye PdM connects to existing data sources while regular machine operation continues as usual. Over seven days, its proprietary algorithms operate in the background to analyze normal machine behavior and historical data if available. It’s then ready to provide insights and power a scalable and sustainable machine reliability program.

We offer a suite of SaaS products and services to support and grow machine reliability and sustainability. To get started on your journey, we offer Senseye PdM Complete, which combines our award-winning SaaS product Senseye PdM with our hands-on Customer Success Management. Senseye ROI Lock® backs Senseye PdM Complete to ensure that deployments achieve at least a 100% ROI within 12 months, or customers will have a full refund.

For mature customers wanting to take charge of their reliability and sustainability journey, Senseye PdM Enterprise allows them to ‘get under the hood and leverage their reliability engineering, condition monitoring, and data analysis expertise in combination with our class-leading technology.

Key to all of our offers is Senseye PdM Omniverse® which provides the tools, knowledge, processes, and community to empower your teams on their machine reliability and sustainability journey. 

Our network of industrial partners, including PTC, Microsoft, Schneider Electric, and Siemens, enables our ability to deliver sustainable savings on a global level. Alongside our delivery partners are Senseye PdM Ready partners such as IFM, Omron, and ADLINK, whose solutions can provide ‘plug and play capabilities for advanced and diverse machine health monitoring.

More information below:

Senseye PdM Complete™ – a combination of award-winning PdM software, with an expert managed service to set up and guide you on the journey to a complete Return on Investment. Senseye ROI Lock™ backs it to guarantee success within 12 months, without you needing in-house data science expertise.

Driven by your in-house expertise, Senseye PdM Enterprise is the leading Predictive Maintenance platform to power your digital transformation. Its flexible and open approach puts you in complete control of your Predictive Maintenance journey, with the best tools in the world, combined with the best possible knowledge of your assets and practices – yours.

Senseye PdM Omniverse is a knowledge platform and community that provides industry operators and partners step-by-step processes, workflows, and guidance to implement successful, sustainable, and scalable predictive maintenance projects. 

Realizing that everyone is at different stages of their maintenance journey, we developed Senseye PdM Stream for some of the more complex data transformations to enable companies to accelerate their maintenance journey and allow them to reuse as much existing data (and investments) as possible.

Senseye Ready is our ecosystem of partner’s products that offer direct integration with Senseye’s predictive maintenance software. It means that your predictive maintenance experience is plug-and-play and allows the very best hardware solutions for your requirements.

Getting started with predictive maintenance can require months of planning and discussions before you take your first step. With Senseye PdM Starter Packs, companies can get started in as little as 14 days. All the hardware you need to start collecting data from your machinery is included, alongside our award-winning Senseye PdM software.

E.E: What was the research behind the products/solutions design?

SENSEYE: Senseye PdM is the result of over 150 person-years of research and development, leveraging skills from industry specialists, condition monitoring experts, and mechanical engineers, in addition to a team

of leading data scientists. Senseye also draws upon its founders’ extensive knowledge and experience in predictive maintenance and machine reliability developed during their time in the aerospace and defense industries.

Everything is supported by our underlying philosophy that Predictive Maintenance and machine reliability needs to result in measurable business outcomes. Our approach is to use AI to work with the human operator, not to replace them – in this way the strengths of both can be combined.

E.E: Which are the key aspects of the process of product/solution development?

SENSEYE: There are three guiding principles on our product and solution development:

Guide attention – The aim of the application is to focus the user’s attention on machines that need it most. The analytics is designed to guide a human operator to where their expertise can make the most impact.

Focus the meaning – All analytics systems require good data, plentiful context, and high-quality algorithms. In the environments where we work, context is a scarce resource and is the thing that places the fundamental limit on how well the algorithms can perform. As such, we focus on:

  • Making our analytics work with the minimum amount of context;
  • Using the application to gather as much additional context from the user as possible;
  • Enhancing context as much as we reasonably can.

Model the user – A key differentiator of Senseye PdM is that the product makes optimal use of scarce context by focusing the analytics on the user, the maintenance professional. This way, instead of only predicting health, a property of the machine, we also predict user interest, a property of the user. We can do this effectively because we have access to the user and can use their feedback to optimize our predictions and model the generic or ‘average’ user. This is an effective way to address the condition monitoring problem in the kinds of low context environments where Senseye PdM is designed to work.

E.E: How quickly do you adapt your products/solutions to different requirements?

SENSEYE: As a company, we work to a standard set of goals defined using a “Hoshin-Kanri” process. These are executed in 8 weeks cycles for all business units to align to a shared vision while remaining agile.  The product development is driven by input from all business areas, providing priorities into the development during the eight-week cycle, enabling technical, commercial, and sales priorities to reflect the product’s direction.

As Senseye PdM is a multi-tenanted product, the product is generally not adapted to specific customer needs, instead we focus on a problem common to many customers across many industries.

E.E: What are the most common requirements from clients?

SENSEYE:

  • Low rate of false positives and negatives;
  • Guidance to transition from reactive to predictive maintenance;
  • A need to be guided on the journey to achieving real business outcomes (e.g., real savings) from their investment in machine reliability and sustainability;
  • Flexibility when integrating to existing systems and workflows – leveraging existing investments;
  • Established and well tested data security compliance.

E.E: How do your products/solutions solve problems that your clients may have?

SENSEYE: We’ve learned a lot about deploying predictive maintenance and related technologies across a variety of sectors. It has been – and continues to be – a learning experience, especially as we encounter different sectors and different levels of customer maturity.

Simon Kampa, CEO of Senseye, comments “Implementing a successful Predictive Maintenance project is difficult, with analysts reporting that over 80% of these kinds of projects have so far failed. Senseye have decades of combined experience of successful PdM implementation and through our Senseye PdM Complete managed service we make this available to our existing and new clients. As it’s backed by the industry-first Senseye ROI Lock®, we guarantee that they’ll see a full return on investment within 12 months or they are entitled to a full refund.”

E.E: Tell us about products/solutions innovation.

SENSEYE: To assist our customers in finding sustainable successes and increasing knowledge in their organization, we developed a best practices framework that can help reduce maintenance costs by up to 40%. This forms a core part of Senseye PdM Omniverse that is made available to all customers and partners – putting their success directly within their control.

A core strategy of what we do is to continue to build on our mature partnership network leading system integrators and monitoring equipment manufacturers so that no-matter the maintenance maturity of our customers, they can benefit from an investment in machine reliability and sustainability with Senseye.

E.E: What are the trends in product/solution design in your area of activity?

SENSEYE: Within the predictive maintenance and condition monitoring area we are seeing that the market is growing and the opportunity is with sectors that have not traditionally had mature maintenance or condition monitoring strategies.  The trend that we are driving forward in our area is towards greater levels of self-service and simplification of the adoption of predicative maintenance., this is both a simplification of the technology and its outputs, plus ensuring that cultural change and adoption is supported.

E.E: What are your estimations for the rest of the year?

SENSEYE: Covid had a dramatic impact on all businesses in 2020 and caused many to restrict planned investments. We see this starting to be relaxed and investments in Digital Transformation technologies (e.g. Industry 4.0 / Industrial Internet of Things) are only below ‘enabling remote workers’ on the outcome / project list that companies are now putting into place.