What is Manufacturing Analytics?

Manufacturing analytics is the new wave of advanced analytics for manufacturing companies and part of industry 4.0. It uses Artificial Intelligence algorithms, Machine Learning modeling, and visualizations to process huge amounts of data and deliver insights that can improve operational performance and profitability.

The process manufacturing industry has lagged behind other sectors in applying advanced analytics, mainly due to the sheer size and complexity of its data sets. Advanced process control (APC) systems have been used to improve productivity for years, but because they are so expensive to run, they’re only used for key assets and processes.

New manufacturing analytics using AI and ML makes it possible and affordable to track, collect, and crunch data from every machine and process, yet intuitive enough for non-data scientists to use.

How can manufacturing analytics help process manufacturers?

Manufacturing analytics open up visibility into every aspect of plant management and production processes. In turn, that visibility enables a new level of optimization and efficiency across the plant, including:

Optimizing production quality:

  • Spot and remove bottlenecks in production systems
  • Respond faster to plant incidents
  • Identify areas where process can be improved with relatively small investments
  • Improve production quality by understanding performance drivers

Refining the supply chain:

Forecasting demand:

  • Prevent overproduction
  • Understand and anticipate customer and market needs
  • Improve product flow and replenishment in warehouses

Achieving OEE:

How can process plants use manufacturing analytics to their fullest extent?

Gather your data in a single location

Process plants generally possess enormous amounts of data, but it tends to be siloed in different systems, frameworks, and formats. Find a data processing platform or warehouse that can receive and store all your data streams and convert them to a single format, so that all the data be accessed at the same time.

Find the right tools

Process plants have unique data processing needs that aren’t the same as those of other industries. You need manufacturing analytics platforms that are accustomed to the demands of a process plant and can cope with the flood of data.

Begin with the areas of greatest impact

Just like with every digital transformation project, you should start applying manufacturing analytics to the areas that have the most inefficiencies or recurring issues, the highest input cost, and/or will have the largest impact on profitability. This way you can prove value quickly and maximize RoI.

Lead a culture shift

Applying manufacturing analytics effectively requires an organization-wide culture change that begins at the top and extends throughout the entire workforce. You need extensive education to engage employees with new ways of accessing and applying insights, while also setting clear goals and realistic expectations.

Map your skills gaps

The chances are high that you’ll need new skills and resources to fully apply manufacturing analytics. It’s crucial to carefully assess which capabilities and resources are lacking, and then create a plan for how to provide them.

Support self-service

Enable all your process engineers, plant managers, and critical staff to tap into deep plant insights independently. Establishing self-service tools that can be used and understood by all of your key workers allows you to spread the data advantage across the organization.

How does manufacturing analytics benefit process plants?

Applying advanced analytics to process manufacturing plants helps you to increase visibility into every process, optimizing them for maximum productivity and minimum waste. By implementing manufacturing analytics, you can improve plant efficiency, achieve operational excellence, drive innovation, and boost profitability.