How Digitech Labs helped this global manufacturing company with Advanced Analytics from Shopfloor Data
At a Glance
A Big 5 Management Consulting firm was brought in by the board of the manufacturing company to implement Industry 4.0 methodologies across all their manufacturing locations. The consulting firm roped in Digitech to implement several technology layers across cloud, IoT, and analytics.
The Context
The manufacturing company made its expectation very clear right from the start. It didn’t want to implement Industry 4.0 methodologies for the sake of it. Rather, in line with Digitech’s philosophy, the company wanted to ensure any technology implementation had a clear business case and a specific purpose.
Having said that, it also wanted to lay the foundation for future growth, so a short-term only solution wouldn’t help. While their short-term goal was to digitize factory operations and use shop floor data better to enable decision-making, the goal was to build an overall digital transformation program wherein this wouldn’t be a siloed effort of gathering data from only factories.
The Solution
In collaboration with the management consulting firm, our data engineering team comprising engineers and data scientists, proposed the following step-by-step approach.
- The first step was to conduct an audit of all shop floor locations and identify what data was already available and what else had to be collected.
- Once this was done, the next step was to identify partners to IoT-enable the manufacturing process. This included talking to equipment manufacturers and our team identifying the right IoT-enabled sensors to add into the workflow.
- Following this step, we checked how the company was feeding data into the company’s ERP solution. Were there any gaps between on-ground data from the factory and data being fed into the ERP. We did a through job of doing a data quality validation process, keeping in mind data governance and data security requirements as well.
- A cloud-based data warehouse was setup on the AWS platform to bring in data from multiple sources, across locations.
- This was further unified with real-time data in the ERP’s Supply Chain Module.
- Using the right data pipeline solutions, we brought together data from disparate sources and got all the data transformed ready for BI.
- Relevant analytical models were built to identify, spot and analyze operational costs, inventory and human resource data, capacity planning, supply chain issues, quality metrics, etc.
- Different stakeholders were given access to specific dashboards relevant for their specific context.
- Our AI team leveraged “big data” that came from the management consulting firm to build models to generate predictive insights.
- Data was presented in a way that it was easy to understand and consume, for various team members and business leaders.
The Outcome
The manufacturing company appreciated Digitech’s approach of sticking to our expertise in cloud, analytics and AI, while leveraging the management consulting firm’s domain expertise and access to data that came in extremely handing to build the AI model.
Some of the direct benefits of this engagement include:
- Both plant heads and executive leaders relied on the Cloud BI solution we built on AWS as the “single source of truth” for all factory data and information.
- Using the data, we were able to offer “next best recommendations” on how to tackle certain issues - especially supply chain-related issues - using our AI models.
- There has been direct cost savings (reduction in supplier costs and reduced wastage because of better demand forecasting) for the client thanks to a data-driven approach towards SCM and inventory management decisions.