What aspects of technical infrastructure do we need to assess?
A Comprehensive Guide for Manufacturers
Use this step-by-step book as your guide to a successful digital manufacturing journey.
Very few manufacturers have all their technical requirements in place at the outset of a digital initiative. It’s important to get an accurate picture of what you’ve already got and what you’ll need to build or buy. Machine connectivity is the primary must-have but there are other technical considerations as well.
The three areas to evaluate are:
Connectivity and Accessibility
At the foundational level, ascertain whether data is being collected from sensors on your key production machines and is flowing into a system of record. Also explore whether you’re measuring and gathering the right kind of data to address your operational goals.
- Are all machines equipped with sensors?
- Are sensors network-accessible?
- Is data streaming into a system of record or database?
- Are you capturing key attributes such as machine downtime, defect data, and part serial numbers or batch numbers with time stamps?
Cloud and Security
With huge data volumes and massive computing power the norm for AI-driven manufacturing analytics, the cloud is far and away the most practical, affordable venue. How prepared are you to migrate production data to cloud-based infrastructure? Security is a key concern, especially in manufacturing sectors governed by regulations requiring special treatment for sensitive information such as classified, ITAR, or HIPAA data.
- Are your system of record (i.e. historian) and other key data sources (ERP, MES, MRO, supplier data) securely accessible from outside the company?
- Do you have policy guidelines for working with cloud providers?
- Are data segregation requirements clearly defined and do you have a system for cordoning off sensitive information?
The project inception stage is not too early to assess your capabilities for working with the data you generate. Do you have the in-house expertise to interpret data streams from machine sensors and how they map to your physical production process? Much of this knowhow will come from blending the skills and understanding of IT with those of your operational engineers. The two sides must work in synergy to define project goals and develop processes to achieve them. You’ll also likely need to source advanced data analysis capabilities through consultants and by creating and nurturing a data-focused specialty within IT.
These requirements trace back to the premise of this tutorial: adopting a “data first” digital strategy to collect and unify your entire universe of production-related data to address a wide range of use cases… rather than pursuing a succession of disjointed one-off pilots that don’t scale to multiple objectives and plants.
Ensure success by focusing on organizational readiness as described earlier. Build a solid foundation by articulating a long-term digital vision, validating how a unified data platform enables it, and securing early and strong support from leadership across corporate, operational, and IT domains.