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Best practices to follow for data science projects in manufacturing industry

Industry 4.0 is a new buzz word among manufacturing industries. But what does it truly mean? As we know industry 3.0 led the introduction of computers and logic based systems to automate manufacturing processes. Even though manufacturing was automated, human input is still required to manufacture and monitor them. This is where Industry 4.0 differs. The aim is to not only automate the manufacturing process, but to automate it without human intervention. e.g. In steel manufacturing manual inputs are provided and changed during the manufacturing process, which is essential for maintaining the required grade and quality of the product. Instead of manual analysis and intervention, an intelligent agent can be introduced to infer the situation based on continuously monitored sensor data and – if wished by the organization - to make suitable changes automatically.

This might raise a first question: What exactly is an intelligent or smart agent?

An intelligent agend is basically a software program which uses machine learning based methods to monitor processes, predict product/ batch quality, machine failures and tool breakdowns (predictive analytics). Additionally, it determines root-causes and most influential parameters and gives recommendations for optimal process parameters(prescriptive analytics). These are then communicated via dashboards, alerts and notifications to the user, enabling him/her to take proactive corrective actions if necessary.

Now the next question would be why should one invest in this. With the help of a smart agent, the user is able to monitor data coming from hundreds of sensors, analyze it automatically and recieve recommendations for decision making with a fraction of time what humans would require. By supporting the human decision making process loop with data based insights into the production, the uncertainty associated with making a decision is reduced and better decisions can be taken which in return leads to higher productivity and yield.

The components of industry 4.0 might have different end goals, but what they do share with each other are data driven approaches being at the core of the service being offered. This is driven by:

1. Digitization and integration of vertical and horizontal value chains:
2. Digitization of product and service offerings:
3. Digital business models and customer access

By now, we hope that you have a bit more clarity about the meaning of what an intelligent agent is and the benefits an implementation can provide to organizations.

In our next articles we will further examine on the introduction of an intelligent agent and provide useful recommendations for every single step in the practical implementation.

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