Data-driven Decision Making in Smart Manufacturing

According to the National Institute of Standards and Technology (NIST), Smart Manufacturing are systems that are “fully integrated, collaborative manufacturing systems that respond in real-time to meet changing demands and conditions in the factory, in the supply network, and in customer needs.”

Smart manufacturing relies on having a setup that is responsive and can adapt quickly to changes in the environment. This integrated responsive setup is powered by robust real-time data which helps evaluate the environment and make necessary alterations in real-time. Much of this data remains in information silos within the factory Integration of the combined data from multiple data sources can improve efficiency and speed up the production processes.

According to the National Institute of Standards and Technology (NIST), Smart Manufacturing are systems that are “fully-integrated, collaborative manufacturing systems that respond in real-time to meet changing demands and conditions in the factory, in the supply network, and in customer needs.
Smart manufacturing relies on having a setup that is responsive and can adapt quickly to changes in the environment. This integrated responsive setup is powered by robust real-time data which helps evaluate the environment and make necessary alterations in real-time. Much of this data remains in information silos within the factory. Integration of the combined data from multiple data sources can improve efficiency and speed up the production processes.
The Manufacturing (MFG) at ARi has been building expertise and support our customers to experience the benefits of data-driven insights into their day-to-day Manufacturing processes.

A Practical Application of Data Engineering at Work

We are discussing below an actual implementation of Data Engineering with the customer-specific identifiers masked for data security.
The ARi team works closely with the customer manufacturing facility to help identify and resolve potential causes for delays in their throughput. Structured and Phased approach of the solution that answers key critical questions at each stage of the business need is discussed below.

Phase 0: Data Readiness

Understanding the process functionality, data availability and cleanliness of data plays a vital role to initiate the process. Ari Manufacturing team

  • Creates a list of data requirements and work with the customer to assess the availability of this data in their systems.
  • Identifies various systems, their respective data sources and work with the manufacturing facility to get access to the data source
  • Access and retrieve the real-time facility data
  • Pass the data collected through data clean-up and filtering stage using custom scripts to provide the cleansed data that powers our investigation at later stages.

Phase 1: Problem Identification & Quantification

Phase 1 is Problem Identification and Quantification that helps answer the following questions,

  • Is there an issue in my current process?
  • If so, is the issue consistent or is it an anomaly?
  • If consistent, is it significant enough to warrant action?

                                                                                           – Article contributed by Raguram Narayanan