In the never-ending quest for profitability, operations managers are always looking for new tools and strategies to stay ahead of the competition. One such solution is manufacturing analytics-a powerful weapon in your toolkit for uncovering hidden insights, streamlining operations and reducing costs. But what exactly do manufacturing analytics solutions entail, and how does it improve profitability? In this blog, we take a closer look.

At its core, manufacturing analytics is the process of collecting, analyzing, and interpreting data generated during the manufacturing process to gain insights, optimize operations, and reduce costs. It’s a multi-step journey that begins with gaining a deep understanding of your business challenges, pain points, and processes and ends with incorporating these insights into your operations for continuous improvement.

Setting up a manufacturing analytics solution involves five main steps:

Project understanding
This initial phase involves immersing yourself in the complexities of your business, exploring challenges and potential value creation opportunities. The outcome of this phase is a well-defined suitable target function describing the business problem to solve. The target function should be driven by impact.

Data collection
You collect data from multiple sources in your manufacturing environment, such as ERP systems, MES data, sensor data, production schedules, and quality control metrics. You then consolidate the data sources and store them in a central location, such as a data lake, to improve data accessibility and quality. This wealth of data serves as the raw material for your analytics efforts.

Model
Armed with data, it’s time to dig deep. Using a mix of statistical and machine learning techniques, you sift through the data to uncover patterns, trends, and insights. The goal? To build a predictive model capable of identifying and quantifying the most influential (cost) drivers impacting your financial performance.

Refine
A fundamental characteristic of manufacturing analytics is the focus on actionable drivers, i.e. parameters that can be actively influenced/controlled by an operations specialist. The key is to inject domain knowledge to guide and refine the modeling effort towards actionable parameters.

Integration
Lastly, the insights derived from your analysis are integrated into your operations to drive ongoing improvement. Perform field tests to evaluate model recommendations and steer implementation initiatives. Through visualization tools for data-driven decision-making or live dashboards for recommending optimal actions, manufacturing analytics becomes an indispensable component of your strategic arsenal.

However, the advantages of manufacturing analytics go beyond profitability. By offering quantified insights into cost drivers like resource usage, waste volume, and energy efficiency, analytics can have a significant impact on promoting sustainability throughout your operations.

Insights obtained from analytics can guide strategies for optimizing resources, improving energy efficiency, and reducing waste, resulting in cost reductions while also decreasing your environmental impact. From enhancing material consumption to managing energy demand and production, manufacturing analytics becomes an asset in your pursuit of sustainable profitability.