GE Software recently participated in the 18th annual ARC Industry User Forum in Orlando, Florida. With a focus on manufacturing, automation, and industrial control systems, the conference brought together more than 800 people from the oil & gas, power generation, mining, life sciences, consumer packaged goods, food manufacturing, and automotive industries.
Based on the event’s over 34 sessions and keynotes, several key trends emerged:
The retiring workforce and what Millennials expect
Today, much of the running industrial equipment is old and has been in production for decades. Similarly, many of the people who maintain and run this equipment have been at it for years and are increasingly retiring from the workforce. This trend brings great loss – of experience, expertise, and “tribal knowledge.
Enter the Millenials (born between the early 1980s and the early 2000s), who are desperately needed to begin careers in the industrial equipment industries. As these Millennial enter the workforce, they have different expectations including:
- They want to work for companies with a social presence, work flexibility, a constant flow of challenging and interesting projects, networks, interaction with senior management, feedback, and recognition.
- They also expect their employers to embrace mobile technology. If they’re in the field, they want their data on a mobile device. They want to train on a mobile device, they want to collaborate with their colleagues on a mobile device.
- Furthermore, heavy industry, process engineering, and manufacturing just aren’t as attractive to this generation compared to other industries such as high-tech.
- Balancing this knowledge drain with attractive job offerings is keeping many HR executives up at night
Predictive analytics for safety
Yes, it’s true that predictive analytics can drive higher asset and operational efficiency, which is good for the business. Because many businesses operate in harsh environments, or are heavily regulated, or both – safety is of paramount importance.
Industrial accidents have been decreasing in number, but their severity is increasing. Operator fatigue, lack of training, and equipment failure are not to blame – instead, it’s complexity of the task the operator is immersed in that increases the risk. This complexity comes from multiple systems that are often connected and highly complex.
Analytics can help increase safety by predicting failures and sounding the alarm before someone gets hurt. Furthermore, presenting information to the field tech on a mobile device while in the field gives better information and line-of-sight into brewing dangers.
Parts on-demand with 3D printing
The way things normally work: Something on your machine breaks, and you need a replacement part. If it’s not in your spare parts inventory, getting it from the supplier can be expensive and may take days to receive. Problem solved – print it!
Manufacturers are minimizing their downtime by printing parts vs. ordering them. While this approach has many advantages, it does introduce new complexities for asset owners:
- Asset management
- Configuration management
Adopting mobile technology
Workers want it (especially the new ones – see Millenials discussion above). Companies see the advantages:
- Delivering information in the field on a convenient form-factor
- Delivering the right information, at the right time, in the right place
- Work gets done faster
- Get immediate help by collaborating with colleagues and customers
People are paying attentioned to augmented reality (AR). For example, AR can help field techs understand exactly where the trouble is by overlaying a symbolic display (graphic) of an alarm location over a photograph of a power plant or specific piece of equipment. Other AR use cases include:
- inventory management
- asset tracking
- collaboration (e.g., chat, video chat)
- video monitoring
- incident reporting
- remote control
But AR comes with certain challenges, including BYOD and security.
The predictive analytics “round-trip”
Predictive analytics provide greater insight into assets and operations. This means things run better, faster, longer. Many organizations are leveraging their analytics in a “round-trip fashion.”
- Assess their environment
- Determine what data to capture
- Run analytics
- Push the results back into their system (e.g., new machine configuration changes, predicting maintenance events, controller changes, operations optimizations, etc.)
But in this model, only the business gets the benefits of the analytics. What about feeding this information back to the machine manufacturer? They, in turn, use this data to build better equipment.