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:


  • As a result of globalization, institutions and companies are increasingly connected and work together more closely than ever before. This results in a need for constant communication and therefore an growing amount of data being captured and transferred between organisations.

  • Vertically, Industry 4.0 coordinates forms over the whole association. For instance forms in item improvement, fabricating, organizing and administration while on a horizontal plane, Industry 4.0 incorporates interior activities from providers to clients in addition to all key worth chain accomplices.


2. Digitization of product and service offerings:


  • Be it through the development of new or the augmentation of existing products, companies’ offering throughout all industries and branches are becoming more and more digitized generating data of increasing volume, variety and velocity.

  • Coordinating new techniques for information assortment and examination for instance through the development of existing items or making of new digitized items, encourages organizations to create information on item use and in this way, to refine items so as to address best the customer’s needs.


3. Digital business models and customer access


  • Arriving at consumer loyalty is a multi-stage, endless procedure that should be adjusted right now as clients' needs change constantly. Consequently, organizations grow their contributions by building up troublesome advanced plans of action to give their clients computerized arrangements that address their issues best.


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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