Product Models

OEM companies offer their customers a variety of products and variants that may differ in characteristics such as power, maximum load, and form factor. Managing these differences efficiently is crucial for providing seamless service and support. 

Now, instead of defining a new Thing Definition for each different model or variant, you can use the concept of Product Model. In this way you are free to define Thing Definitions to reuse elements as you like, taking advantage of inheritance. Product Models, instead, can be defined in the same way your public product catalog is organized, and the same Thing Definition can be reused across different product models.

This structured approach ensures streamlined management of different product offerings, facilitating easier updates, maintenance, and scalability of the product catalog which is thus decoupled from the Thing Definition abstraction process.

By using product models, in DPS the concept of Thing Definition is totally hidden from users who are more familiar with the model names provided by the OEM.

Spare Parts

Physical products are composed of many parts (e.g. bearings, screws, filters, joints), which can be subject to wear and tear or failure. To minimize machine downtime, a way to quickly find and order a replacement part can be offered within the DPS by defining Spare Parts and associate them to Product Models.

In the Console within the catalog you can now configure all the spare parts that are used by products.
A Spare Part is defined by a code, a name, a description, and optionally you can attach images.

In the DPS, a dedicated view helps users find spare parts by model, and technical schemes reduce the risk of buying the wrong part.

SMART SPARE PARTS & CONSUMABLES

Order management

In addition to searching, your customers can also purchase parts directly from DPS. Once they have identified spare parts, they can add them to the shopping cart and proceed with the order while remaining in the same seamlessly application.

The Store page has been enhanced with a section where users can review and monitor the progress of their orders. 

An order can be addressed to an Organization or a Partner, so also your partners become spare parts dealers. When an order is created, an order management flow takes place that includes several actors and steps, from order creation to delivery of the purchased products.

SMART SPARE PARTS & CONSUMABLES

Wear monitoring

Monitoring the wear of your machines is critical to avoid downtime, and even worse, breakdowns that are costly to repair.

In the console you can now define Wear Metrics that are based on predefined or custom wear algorithms. For instance, you leverage use the time-based wear computation algorithm that uses the machine working time insight.

Like other insights, such metrics are periodically computed and according to thresholds the DPS user is notified with specific alerts and replacement actions.

A new set of widgets can be used to effectively display the wear status of various components.

The replacement action can be enriched by the set of parts to be replaced, with a shortcut to add them quickly to the shopping cart and complete the purchase.

Thanks to this feature, operations managers can be notified in advance of parts to be replaced. Direct and contextual purchasing not only increases sales, but also reduces the time for spare parts procurement and thus reduces machine downtime.

This operating model is called Machine Customers, which at this stage still requires manual intervention by the customer to complete the order; in the future it may be fully automated, i.e. the machines will purchase the parts themselves.

VALUE-ADDED DIGITAL SERVICES,SMART AFTER SALES & ADVANCED SERVICES,SMART SPARE PARTS & CONSUMABLES

Uptime, Downtime and Working Time Insights

A new set of algorithms can be used to measure how the machine spends its operating time.

• Uptime: measures the time a machine is operational.
• Downtime: measures the time a machine is not operational or unable to perform due to various reasons such as maintenance, repairs, malfunction, or other issues. 
• Working Time: measure the time in which a machine is actively performing its intended function, such as production, processing, or normal operation.

These algorithms generate various outputs that can be used with Insight Metrics, the values of which can be displayed on dedicated pages depending on the person accessing the DPS.

These new indicators are helpful to operation managers to identify how well a machine is used by the operators, and determine if there are inactivity periods. Service managers can analyze and compare downtime to proactively propose maintenance activities to reduce and prevent failures. 

VALUE-ADDED DIGITAL SERVICES,SMART AFTER SALES & ADVANCED SERVICES

Bug fixes (DPS)

• In the recipe list widget the Choose file button was disabled after exporting a recipe.
• ADDRESS and CITY type properties were not displayed correctly in the advanced search panels for customers and locations.