Data, the most essential element in Industry 4.0

In previous blog, I made the argument that decision-making is the core of Industry 4.0 and I would like to discuss more about “data”, the most essential element of Industry 4.0

In order to make decisions, we will examine many different data, for example, when we want to decide how much to make, we check the sales history, we check open orders, we check inventory, WIP…internal data and also refer some external data such as market status, competitor information…so that we can make the decision of “how much to make”. Without data, we cannot do any analysis and hardly make good decisions. Therefore, I believe data is the most essential element for decision-making and Industry 4.0.

Some might ask, Why automation? Why IoT? Well, I will say, that is the way we collect data. In old days, we relied on operators to input transaction data in transactional systems (MES, ERP…) to record activities (data of activities). But are the data real-time? are the data reliable? If all the data are automatically fed into system via these automation systems, users can expect more real-time, reliable data. Before IoT, some of the data are not available or hard to be obtained, for example, logistics information such as truck movement. This information can be updated only when truck arrives and the driver reports his duty. With IoT, more and more “things” can be connected, people can get more data for making decisions. Because of range of data availability, the quality of decision, speed of decisions can all be improved. When decisions are made, the instructions (actions) also need to be sent to execution and again how the instructions are sent is also improved due to automation and IoT.

Because of data drive all decisions, I think how to manage data, use data, analyze data is the key to success for Industry 4.0. If enterprise wants to be “Industry 4.0”, they need to think about how they will do with data.

If the enterprise does not have the capability to collect, store data, it needs to start with the capability to collect/store data related its activities. And it needs to think what kind of data is required to support their business decisions.

Enterprise which has data needs to think about how they can analyze the data, build its analytics capability (from descriptive to prescriptive). This part is a process of evolution, needs to be adjusted, calibrated with more and more data collected, more and more results obtained.

No matter which stage the enterprise is, what capability the enterprise has, the common and fundamental part is to have a good data platform to hold, store data and support analytics. The platform shall take transactions, integrate with automation, work with IoT, support Big Data, collaborate with Cloud…

So, want to go “Industry 4.0”? Think about the data first, think about data platform first.

Decision-Making, it's what Industry 4.0 is all about

What is Industry 4.0? Is it "smart factory'? Buying robots, automating production...is that what makes the enterprise "Industry 4.0"? Let me take a step back.

Enterprise makes all kinds of decisions during its operations: How much to sell? How much to make? What to sell? To whom to sell? Where to store? How to make?....all kind of decision and all kinds of actions followed.

To my point of view, Industry 4.0 is merely talking about how to make decisions related to productions fast and in the way applying new technologies such as IoT, Big Data (Analytics), Cloud. But in the end of day, it still comes to "Decisions".

With data collected and analyzed in real time fashion, machines can self-decide what to do next. For example, here comes a lot and machine reads its RFID to know the following operation required for this lot, (make decisions) download process recipe, start the operation (take actions). So, I think Industry 4.0 is all about how to automate the decision process without or with limited human input to improve production efficiency, reduce energy consumption, improve working environment.

Data, analysis, decisions, actions are the steps for enterprise to manage its daily operations. Because of maturity of the enterprise, enterprise might have different levels of human input during the analysis step.

If enterprise can only get "what was happening" from their data, they need high level of human input to make decisions. From my experience, production planners download production reports, manipulate those data in Excel then decide the next production plan. So, lots of human input here. This is "descriptive analytics", very basic.

Some enterprise are able to present "why did it happen" using some business intelligence tools. They can know the root cause then decide what to do next. For example, planners drill down the reports and find out one of the machines is the bottleneck, causes WIP to pile up. Planners can then decide how to offload and make sure orders still meet the due date. Less human input then stage one, this is "diagnostic analytics".

Applying some statistical models, enterprise can find out "what will happen" so they can decide to take some actions before it happens. Planners forecast incoming demand by looking into forecast numbers generated from historical data and decide the master production schedule accordingly. This is "predictive analytics".

Three stages need human inputs to make decisions, most of the time, by "experience". Therefore, it could be less efficient and hinder the responsiveness.

If some sort of "intelligence" can be applied to make decisions for human, then it can greatly improve efficiency. This is "prescriptive analytics" and is what Industry 4.0 aims for. However, there are still 2 levels of this stage, one is the "intelligence" only helps human to make decisions (decision support). For example, advanced planning system generates production plan via the data but planners still need to make final decisions for execution. The next step is really what Industry 4.0 talking about: automate decision making. Just like Jarvis in Iron Man movies, it can make the suits based on input from Tony Stark (closed color, materials) without Stark oversees the production processes.

Back to my argument, Industry 4.0 is talking about making production-related decisions in better way, faster way and automates decisions where it's possible and efficient. Therefore, to start with Industry 4.0, enterprise needs to think about how their decisions will be made then lay out the plan to enable the decision processes.