we.CONECT: The pop in your job – you work as Program Manager, Smart Manufacturing at Corning – which tasks would you highlight as particularly interesting? What is most exciting about your role, and why are you passionate about your job?
Grethel Mulroy: There are so many things I like about my role- problem-solving – but also the ‘big picture’ aspect of looking at a problem beyond the immediate factory need but also as a foundation to enabling Industry4.0 tools and practices. I like the change management aspect of exploring and implementing new technologies ; the technology itself, but also the adoption/human aspects, both for users and even for the team that is implementing. It’s exciting to be on the forefront of technology that can change the way we work- allow us to do more than we could before, allow us to know more than we could in the past- the ability to influence and shape that future is very motivating.
we.CONECT: During your “Challenge Your Peers” session you will raise the question Data management – the backbone of your Industry 4.0 projects at Industry of Things World USA. Has data management always played such a crucial role for companies or has this changed in the past?
Grethel Mulroy: Data management is much more important now than ever before because of the amount of data, the ways in which we are using it, and the variety of sources where it’s coming from. It has always been important, but easier to manage in the past when it was used for a specific purpose- like machine control, and was contained within one piece of equipment or process. Now that data has multiple uses and users, it’s critical that we have ways to ensure that the data is sound; as they say, ‘garbage in/garbage out’.
we.CONECT: What are the biggest difficulties in this regard and does the way data is managed not grow/ adapt automatically to its determination?
Grethel Mulroy: The difficulty is driven by the complexity- there are many different systems we use to capture data, and they are all different formats, naming conventions, frequency of update, etc. Also, these systems feeds and tags associated with them were set up by People that most likely had an intended use in mind. So their methodology was optimized for that purpose. As we develop more uses for the same data (ie I want to analyze the effect of mfg process step 3 and 4 on the final inspection results from step 17….) then that may be difficult because of the way that data was structured (ie. There’s no link between process step 3 and inspection step 17, because product ID gets added at process step 10…). We might be able to anticipate some of this when designing completely new manufacturing plants and processes, but much of what we work with is existing/ legacy systems and plants so this is not always resolved easily, seems to be more of a case by case basis.
we.CONECT: From your point of view and experience, what are the best approaches to mastering these data challenges?
Grethel Mulroy: I think just having a data management strategy or approach goes a long way; guidelines and rules and processes that are consistent. Data management ‘owner’ – someone whose responsibility is to put systems and processes in place to ensure that data is accurate and consistent, is a plus- may even be essential in some cases. There are also tools that can help safeguard, though I am not as well versed on these. We are still learning in this area and I look forward to hearing what has worked well for others!
we.CONECT: What new possibilities does 5G offer, especially for supply chain transparency?
Grethel Mulroy: 5G will enable us to use more IOT devices more easily than we do today, and in more ways than we do today. The reliability, lower latency, longer battery life, higher bandwidth are all attributes that will open up new uses and data streams that were difficult or expensive to implement before. Also, 5G is enabling an architecture whereby the data computation or analysis is occurring at a central point like a mobile edge computing server or the cloud, which can reduce the complexity and cost of the IOT device itself. In the factory and across the supply chain, we can add more visibility to the manufacturing process, and the movement of product. For the supply chain in particular- finer detail to the location and condition of product through asset tracking sensors, can allow faster response and remediation to issues, and reduction of safety inventory that we typically carry in all parts of the supply chain to buffer when Murphys law hits. Imagine knowing that product being shipped to your customer has experienced a sudden vibrational shock – could be an accident enroute for example- and knowing that there is a high probability this is now defective- so needing to get other product routed to that customer, reacting even before the customer knows that a problem happened.
we.CONECT: Industry of Things World USA is a highly interactive networking event – which conversations are you particularly looking forward to?
Grethel Mulroy: Hearing about what others are doing with cellular technologies and 5G; successes and challenges with managing data across multiple systems and tools, and deploying machine learning in manufacturing or ongoing/ real-time settings.
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