As we mentioned in the previous step, the market offers a number of solutions for data collection from production sensors and other instrumentation. Well-known names in Industrial IoT are represented, such as IBM, SAP, PTC/ThingWorx, Oracle, and others. These products do a good job of aggregating data from a variety of sources. However, that’s as far as they go.
None of these IoT leaders offer a scalable platform for the all-important second phase of manufacturing analytics: contextualizing and modeling the relationships between data and production processes. So while it’s great to have a data lake, if you don’t also have an engine to turn all that information into actionable insight, you’re not gaining much business value.
To build a unified data platform for manufacturing analytics, it’s necessary to explore beyond big names and basic data acquisition products.
Here are some key questions to consider when evaluating solutions and vendors:
- Is the platform comprehensive enough to factor in multiple types of manufacturing processes and machines? (Even continuous process manufacturers have discrete process needs for boxes or other containers. You need an analytics platform that can handle that as well.)
- Can the platform incorporate real-time streaming data?
- Does it scale to a full range of use cases, enterprise-level production volumes, and multiple plants?
- Is the platform designed to create integrated data models from thousands of inputs and multiple data types?
- Does the solution readily integrate with data acquisition, analytics, and visualization tools you may already have?
- Are data and analytics output exportable so they can be utilized elsewhere?
- Does the platform offer workflows, alerting, and integration with production-related systems?
- Does it provide visibility and viewing tools relevant to all levels of the organization, so everyone from operations engineers to supervisors and corporate leaders can draw on the same source of truth?
- Is the solution scalable and software-centric? Or is it a services-led approach that requires repeated consulting engagements every time you need something done?
- Does the platform come with self-service tools that let your engineers build their own applications on top of the system foundation?
- Does the vendor have configuration and support specialists who understand the relationships between specific data inputs and production processes?