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Predictive Maintenance for Machine, Equipment and Device suppliers

The business case for suppliers to collect data from their products at customer sites and offer an enhanced service program is often very strong. With the right data the supplier can offer optimized service programs that give customers increased uptime and lower support cost which they are prepared to pay a premium for.

Besides increased customer satisfaction, a more competitive offering and increased service revenues, the supplier can also gain lower production cost for the support program, less warranty claim issues and data insights for product improvements. But there are also threats to consider - the competitive pressure is also high. If you’re not doing this and your competitors will, how will that affect your future sales? These strong arguments are key reasons why Predictive Maintenance is one of the top use cases for Industrial IoT.

The challenges are however many. How to collect and manage data from a large number of remote customer sites? How to deal with multiple generations of products and different product models, different hardware, protocols and PLCs? Sensor-rich products generate too much data, how can we collect only the relevant data? How to deal with limitations in connectivity and bandwidth? How can we keep the cost at a reasonable level?

Edge Computing addresses these and many other challenges.

Product as a service - change of business model for Machine, Equipment and Device suppliers

Welcome to the Subscription Economy! The subscription business model and pay-per-use has moved and transformed consumer services and the software industry. Now we see a strong trend within Industrial Product-as-a-service where there is a significant upside of new value.

If you can connect and collect the data from the products at your customer sites then you can increase your potential business, first by increasing the uptime with the help of Predictive Maintenance and then by charging by subscription or usage.

The foundation is a rock-solid collection of the data and ability to run distributed data processing on the product itself using Edge Computing technologies.

Predictive Maintenance for Manufacturing, Energy and other asset-rich businesses

Your business has critical machines, equipment or other assets where the asset uptime significantly impacts your revenue or costs. You are in manufacturing, energy, oil, gas, transportation, commercial real estate or other asset-rich sectors.

You have typically a multi-vendor environment that makes it difficult for a single supplier to help you so you need to take ownership yourself. You understand that collecting data from the assets will help you enable Predictive Maintenance and gain control over your assets, operations or processes.

Your challenge is that you have sensor-rich assets and you need to collect the right data. Collecting all data would be both very costly and impractical. Edge Computing enables you to ensure smart data collection so you can succeed with your Predictive Maintenance.  

Manufacturing Yield Optimization

There are several sub-processes in your manufacturing and you see an opportunity to increase your yield by using real-time data to detect quality issues much earlier in the process.

What if you could detect bad quality raw material based on color, shape or size and in real time be able to sort this out, what business impact would that have? Or, if you could use other sensor data to calculate units that need to be scrapped or reworked earlier?

Using Edge Computing allows you to process all data in millisecond, on-site, and have low latency M2M triggers based on your business rules. Across multi-vendor PLCs.

Smart job sites

Connecting people, vehicles, machines, tools and assets at construction, development, repair or other job sites can create significant business and worker safety advantages.

Falls, being caught between objects, electrocutions, motor vehicle crashes and being struck by objects are common, but far from the only, safety hazards at job sites.

Business challenges includes; high cost of equipment failure from stand-still, urgent repairs and delays, asset and inventory tracking, energy conservation.

On-site edge computing is an enabler of real-time monitoring of workers in relation to hazard areas or moving vehicles/objects, tracking of assets and inventory, Predictive Maintenance and more.

Real-time Event-driven Enterprise Integration

We are moving towards a real time world. As consumers we expect immediate actions and get annoyed when messages and notifications are delayed. In the corporate world of digital transformation real-time integration of different data sources is often a foundation.

When streaming sensor data from machine sensors is to be integrated with OT data and enterprise systems, either on-premise or cloud based, low latency is required.

On-premise Edge Computing solutions can enable a faster, more flexible and easy-to-deploy real-time integrations.

Use Cases Section

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