India: Brand Of Intelligence Manufacturing

Last Updated: 20 November 2018
Article by Rishabh Tripathi

Intelligence Manufacturing is a method in which the combined intelligence of people, processes and machines, is used in order to impact the overall economics of manufacturing. The purpose of intelligence manufacturing is to optimize manufacturing resources, improve business value and safety and reduce waste- both on the floor and in back office operations. Manufacturing is a multi-phase process in which new products are created by using raw materials whereas intelligence manufacturing employs computer controls and high levels of adaptability. Manufacturers use latest manufacturing execution systems (MES), intelligent devices, machine-to-machine communication and data analytics for its production lines and facilities in order to achieve the goals of intelligence manufacturing.

Intelligence manufacturing is used for optimizing concept generation, production and product transaction. It is a subset of manufacturing which takes advantage of advanced information and manufacturing technologies in order to enable flexibility in physical processes to address a dynamic and global market.1 Intelligence manufacturing is aimed to create a flexible manufacturing processes that does not cause any harm to the environment and respond rapidly to the changes in demand to the firm at low cost. With intelligence manufacturing, the products are designed for efficient production and recycle-ability and, thus, necessitate a life-cycle view.2 Intelligence manufacturing enables to access information about the manufacturing process. It helps to provide data in the form that is required by manufacturing supply chains, complete product lifecycles, small, medium and large enterprises. The Smart Manufacturing Leadership Coalition (SMLC) is building the technical and business infrastructure that facilitates the development and deployment of Smart Manufacturing systems across the entire manufacturing ecosystems.

Intelligence manufacturing uses internet connected machinery to monitor the overall production process of a factory. The aim of intelligence manufacturing is to identify opportunities for automating manufacturing operations and use data analytics to improve the overall performance of the manufacturing process. Intelligence manufacturing has the ability to regulate manufacturing of the product within the design specifications.

Intelligence manufacturing can be achieved in three ways:-

  1. Existing manufacturing processes can be made intelligent by adding sensors to monitor and control the state of product being processed.
  2. Existing manufacturing processes can become intelligent by monitoring and controlling the state of product being processed.
  3. New processes can be intelligently designed to produce parts of desired quality without the need of sensing and control of the process.

Tools used for Intelligent Manufacturing

The tools used in Intelligent Manufacturing are:

  1. Case Tools
  2. Simulation Algorithms
  3. Neutral Net works
  4. Fuzzy Logic
  5. Genetic Algorithms
  6. Artificial Intelligence

Stages of development of sub-systems of IMS

S. No.



Tools Used


Design Stage

Development in Progress

CAD modeling tools i.e. Auto CAD


Prototype Stage

Developed according to demand

Case Tools with CBR


Procurement Stage

Developed with on live technologies to cater for JIT with vendor certification

Any vendor interactive software


Process Stage

Scheduling tried out with
"   Genetic Algorithms
"   Case based Reasoning

Genetic Algorithms
"   Case Tools
"   Fuzzy composite logic tools


Machining Centre

Artificial Intelligence tried out, in progressive stage of development


Material Handling

Developed with incorporation systems of AGVs, guidance of AGVs & sensors being developed


Storage system

Developed with inventory expert systems



Developed according to inputs received from marketing parameters i.e. demand

Fuzzy Logic + simulation algorithms

Aims and Benefits of Intelligence Manufacturing

The aim of intelligence manufacturing is to utilize data to develop intelligent technology to expedite new and higher quality goods. Intelligence manufacturing involves integrations in all steps of the product fabrication process and aims to become an idealized practice in manufacturing.

  • Emerging Business Practices

The primary goal of intelligent network of manufacturing is to make business models more flexible, adaptive, and reactive approach to participate in competitive markets. If intelligent manufacturing is adopted, it will help the business models to conceptualize around the integration of every step of the development process; invention, manufacturing, transportation and retailing. Thus, a proper implementation of intelligence manufacturing can influence businesses both domestically and worldwide, the companies may also be forced to adapt or adopt the practice to compete, further stirring up the market.3

Apart from smart manufacturing, 'smart business ventures' lays focus on establishing a network, also referred to as Internet of Things (IoT) of multidisciplinary professionals including scientists, engineers, statisticians, economists etc.4 

  • Eliminating workplace inefficiencies and hazards

The adopters of 'intelligence manufacturing system' focus on efficiency optimization which can be done through data research and intelligent learning automation. Therefore, surveying workplace inefficiencies and assisting in worker safety are the important attributes of smart manufacturing. For e.g. Company provide operators personal data access cards with inbuilt Wi-Fi and Bluetooth, which can be connected to the machines and a cloud platform to determinewhich operator is working on which machine in real time.5 Thus, an intelligent, interconnected smart system helps to identify inefficiencies through failed or delayed performance targets.6


1 Davis, Jim; Edgar, Thomas; Porter, James; Bernaden, John; Sarli, Michael (2012-12-20). "Smart manufacturing, manufacturing intelligence and demand-dynamic performance". Computers & Chemical Engineering. FOCAPO 2012. 47: 145–156.

2 Shipp, Stephanie S. (March 2012). "Emerging Global Trends in Advanced Manufacturing", Insititute for Defense Analysis. Retrieved April 2016.

3 Mckewen, Ellen (2015-07-28). "What is Smart Manufacturing". CMTC Manufacturing Blog. CMTC. Retrieved 2016-02-17.

4 Louchez, Alain (January 6, 2014). "From Smart Manufacturing to Manufacturing Smart". Automation World. Retrieved 2016-03-04.

5 "ThingTrax". ThingTrax Connected Manufacturing. London. Retrieved 11/01/2017.

6 Jung, Kiwook (2015-03-16). "Mapping Strategic Goals and Operational Performance Metrics for Smart Manufacturing Systems". Procedia Computer Science. Elsevier (44 p.184-193). Retrieved 2016-02-17.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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