Automating the Future of Manufacturing Plants
Redefining Supply Chain Management
The Industrial IoT Attack Surface
Be Change Ready in an Evolving Manufacturing Vertical
Machine Learning in Manufacturing: Moving to Network- Wide Approach
Paul Boris, CIO - Advanced Manufacturing, GE
Make Manufacturing Cool Again
By Oliver Perez, EMI Manufacturing Technology Director, BD
By mid-20th century, data out of manufacturing was reserved to the engineers, to the only people capable of making sense out of it and providing a diagnosis on a machine malfunction, product quality or a production planning situation. Islands of local information acquisition and processing were born across the manufacturing floor. At that moment, the mechanical power had an ally in the electronic devices that provided a primitive sensing and capacity of processing information giving birth to industrial automation. Workflows were simplified and production lines were revamped with automated solutions to make a single massive, unique, and cheap product over and over again. Productivity gains started to shift from human labor dependent to asset dependent, and manufacturing models such as dedicated factories were born.
It was clear that by the end of the 20th century, the mechanical actions used to transform raw material into finished goods were mastered. A single product could be made in large volumes faster and cheaper than ever before, by controlling the flow of information using Programmable Logic Controllers (PLC) as the orchestra director instructing machines what to do, and in what order in a simplified automated line.
Productivity gains started to shift from human labor dependent to asset dependent, and manufacturing models such as dedicated factories were born
Now that we know why we need to reinvent manufacturing, let’s ignite this revolution inside your company; let’s discuss the changes that need to happen within the walls of the factory.
I mentioned cyber-physical solutions. In this context, what the word solution entails is a symbiosis between the digital and physical domains. A solution that goes back and forth taking the best of both:
Physical to Digital – The purpose is to capture the sea of data from the production floor in order to convert it into digital information. These flows of digital information are then used by software entities to control and improve manufacturing: SCADA, MES, etc. Augmented reality, for example, allows production crews to combine these two domains in real-time to accelerate learning curves, simplify maintenance or facilitate quality inspections. Now imagine that you scanned your entire factory and have it in your virtual world—you can plan and simulate all your changes without moving a physical asset in the floor. Engineering changes literally took another dimension.
Digital to Physical – The purpose is to create algorithms to manipulate information and take decisions that trigger action at the floor level. When you have a 3D model of a component or a fixture, for example, you take that model from your computer to a physical object which eliminates intermediaries, speed up your prototyping cycle, and vertically integrate part of your supply. But above all, it gives you an autonomy that you didn’t have before. 3D maps of your factory are used for autonomous robots which optimize routes in real-time and avoid collisions while transporting material.
Digital to Digital – The purpose is to manipulate information to reveal meaning. Using Big Data to unveil mean time between failures in predictive maintenance or using advance analytics to expose non-obvious trends that could cause shortages of material or product delivery issues are examples in this domain.
Needless to say, all big companies have already started this manufacturing technology expedition. Some have clear strategies while some others have good ideas. But all of them require the support from their leadership. They call it Smart Manufacturing, Advanced Manufacturing, e-Factory, Factory of the Future, Industry 4.0 or Manufacturing 4.0. It really doesn’t matter, at the end they all look for larger profitability pools, competitive advantage, and a lot of fun.