Author : Veeresh Dharappanavar
Manufacturing Data Analytics capabilities are the foundation for a successful Industry 4.0 initiative for the discrete manufacturing industry
Since the introduction of the Fourth Industrial Revolution (Industry 4.0) by Klaus Schwab, the Founder and Executive Chairman of World Economic Forum and the German Government few years ago, efforts have been made to create a framework to push forward the process of digital transformation within various sectors.
To begin with, many organizations globally referred to this framework to map it with their processes and started taking smaller steps to implement digital transformation initiatives and also started looking at peer organizations who already implemented such initiatives. This included attending Smart Industry / Industry 4.0/ Digital Transformation events or speaking with technology companies to understand the successes and learnings. They would then refer to the framework created by the German government and try to map their processes with the guidelines.
Although the Industry 4.0 initiatives makes it possible for companies to gather and analyze equipment and process data, the fundamental aspects of the equipment data availability was missing (especially for the Discrete & Batch Manufacturing sector). Further, the IT & OT systems that these companies had were in silos.
The first step that these organizations would think of was identifying a Plant/ Line or Cell which had the maximum challenges for an Industry 4.0 pilot implementation. This pilot initiative was selected keeping in mind quicker specific business benefits, Return on Investment (ROI) and visibility across the organization.
The next step for the Discrete Manufacturing companies was to solve the Data Availability problem by Automation (adding sensors/ hardware), integrating various Systems like Quality, ERP, and CMMS with Equipment data hence, creating a manufacturing data lake.
How Manufacturing Analytics can help
The manufacturing data lake provides rich insights, which are in the form of manufacturing analytics. This creates provided optimum visibility into manufacturing processes and brings various benefits. This includes benefits such as Overall Equipment Effectiveness (OEE) improvement, monitoring equipment availability, utilizing capacity to the optimum, improving operator efficiency and providing visibility into downtimes along with reasons to enable them to take appropriate actions. Most importantly, this initiative enabled various departments to be on the same page with respect to organization operations.
This also provided organizations with the flexibility to map the available data with various parameters. This included mapping the equipment data with Production Batch, Process Parameters, Utility (Steam, Energy, Gas, Water etc.), and Quality Data to identify specific problem areas and conduct a route cause analysis to mitigate the issue
Once the pilot initiative was completed, organizations took the route of implementing this across the plant, then moving towards multiple plants and in some cases extending the platform with their key suppliers. This generated tremendous value for their organizations by increasing productivity and saving costs.
Today, organizations can make use of manufacturing analytics as a service to bring improvements in productivity and energy efficiency. This can be leveraged using a pay-per-use model with no additional CAPEX, and executed on an outcome based model with assured ROI. More importantly, in a discrete manufacturing setup, organizations can use manufacturing analytics to answers critical questions such as:
What is the probability of us hitting our production target?
Why is a particular machine underperforming?
What is the availability of a set of machines in a specific production site?
Manufacturing analytics can also help discrete manufacturers fulfill the demand for customized made to order products.
In a discrete manufacturing setup, where different components are moving on an assembly line, manufacturing analytics can provide discrete manufacturers with the required intelligence to take critical decisions.