4 Posts
Hi Ben,
Can you speak about the changes that you see for technology? If you can provide examples and how each will transition in the future and for what reason that would be greatly appreciated.
Thanks!
Mason
Can you speak about the changes that you see for technology? If you can provide examples and how each will transition in the future and for what reason that would be greatly appreciated.
Thanks!
Mason
1 Replies
8 Posts
Hi Mason,
Thanks so much for your question! I see several key technology trends:
1. The shift to cloud. The cost of cloud computing has never been cheaper in terms of data storage, collection, analysis and visualization tools. I see this trend increasingly penetrating into the supply chain & manufacturing space. Today an average manufacturing plant produces terabytes of data per annum. In the past it would have been cost prohibitive to put this into the cloud but with storage costs coming down this will become increasingly feasible to have equipment data pumped to the cloud through an IoT Gateway, which will allow for the deployment of supply chain control towers that can coordinate resources and deploy in real-time from a central location.
2. Autonomous Analytics. There is an consistent improving sophistication I have seen even in the last 2 years with regards to analytics solutions that can easily scale within an enterprise. There has been a lot of hype here, but algorithms today are still not about to replace complex un-bounded human decision making in the near term. But in processes that are more bounded, tools like advanced process control algorithms have shown strong promise in automating decisions. The average APC improves process control 3-15% depending on the base process and sophistication of the APC analytics engine. One key point to note here though - is that analytics is only as good as the available data and to avoid the pitfall of throwing analytics at problems without first having a data strategy
3. Robotics are increasing penetrating manufacturing but despite the hype of machine learning full embedment into robotics to enable more dynamic decision making at a scale-able cost is foreseen to be several years out (2025 according to Lux Technology White Paper)
4. Mobility - solving problems anywhere anytime. Mobile apps are nothing new but the companies that have moved the furthest in this space have developed their own internal app stores with development teams (both internal & external).
5. Sensorization costs have come down exponentially allowing us to collect data and organize data that before was highly manual or "dark data" that was either not collected or utilized to drive decisions. Miniaturization of sensors will further the applications of sensors to collect data and improved edge analytics tools will help provide real-time control of those sensors.
Best,
Ben
Thanks so much for your question! I see several key technology trends:
1. The shift to cloud. The cost of cloud computing has never been cheaper in terms of data storage, collection, analysis and visualization tools. I see this trend increasingly penetrating into the supply chain & manufacturing space. Today an average manufacturing plant produces terabytes of data per annum. In the past it would have been cost prohibitive to put this into the cloud but with storage costs coming down this will become increasingly feasible to have equipment data pumped to the cloud through an IoT Gateway, which will allow for the deployment of supply chain control towers that can coordinate resources and deploy in real-time from a central location.
2. Autonomous Analytics. There is an consistent improving sophistication I have seen even in the last 2 years with regards to analytics solutions that can easily scale within an enterprise. There has been a lot of hype here, but algorithms today are still not about to replace complex un-bounded human decision making in the near term. But in processes that are more bounded, tools like advanced process control algorithms have shown strong promise in automating decisions. The average APC improves process control 3-15% depending on the base process and sophistication of the APC analytics engine. One key point to note here though - is that analytics is only as good as the available data and to avoid the pitfall of throwing analytics at problems without first having a data strategy
3. Robotics are increasing penetrating manufacturing but despite the hype of machine learning full embedment into robotics to enable more dynamic decision making at a scale-able cost is foreseen to be several years out (2025 according to Lux Technology White Paper)
4. Mobility - solving problems anywhere anytime. Mobile apps are nothing new but the companies that have moved the furthest in this space have developed their own internal app stores with development teams (both internal & external).
5. Sensorization costs have come down exponentially allowing us to collect data and organize data that before was highly manual or "dark data" that was either not collected or utilized to drive decisions. Miniaturization of sensors will further the applications of sensors to collect data and improved edge analytics tools will help provide real-time control of those sensors.
Best,
Ben
