Control manufacturing process performance with machine-data reports
Is the team responsible for manufacturing processes, or does the company use different types of machines to produce goods? Machine data needs to be collected continuously rather than exported to Excel only when an unexpected problem occurs. We provide working methods and solutions for companies in this situation. We automate machine-data acquisition, store that data securely, and build reports that show both the current condition and a broad analytical view of the manufacturing process. We adapt the solution to the company’s needs and bring extensive experience from work with manufacturers across industries.
Working with data and looking for better business decisions? Schedule a free analytics needs consultation. We will identify the areas that require improvement and select the right solutions.
Manufacturing reporting problems often result from the lack of an end-to-end solution
Reporting for manufacturing companies differs significantly from the business data presentations familiar from sales, finance, or marketing. A project often succeeds only when it covers the entire data lifecycle, from acquisition at the machine to reporting on a Business Intelligence platform. This end-to-end scope consists of several elements that we have defined as separate products in our portfolio. When we establish the project framework and final proposal, we use ready-made components and continuously map our team’s capabilities to them, enabling fast and effective task management at every stage.
Five steps to data-driven manufacturing management
Manufacturing is not the only industry where we use this approach, but it is certainly one of those in which building reports also requires a multistage process covering:
1
Acquisition
2
Cleaning
3
Storage
4
Integration
5
Effective data visualization
Although these stages look standard compared with more common analytics areas, the specific nature of data from different types of machinery means that each stage requires a much broader scope of work.
Machines speak the language of data. We build custom connectors that keep the communication continuous.
Ready-made components rarely provide access to the machine data required for analysis. In sales, marketing, logistics, and many other areas, data is stored in popular databases such as Oracle, SQL Server, Snowflake, or similar systems. Reporting tools generally provide predefined connectors for them. With machinery, a project most often starts by building a connector from scratch. This automates data retrieval and eliminates intermediate layers such as Excel tables or other spreadsheets. The first stage therefore often involves a developer who builds and provides a connection to machine data. We discuss similar connectors in the article about custom data sources in BI systems.
Cleaning and correctly interpreting machine data
Cleaning this type of data is as demanding as acquiring it. The tables obtained for analysis usually contain very raw, technical information that requires documentation review and collaboration with the appropriate team at the client’s company. That team’s input is essential to understanding which data matters, what represents noise, how planned and unplanned downtime is recorded, and many other specific characteristics.
Integrating data from multiple machines and controlling the entire process
Data integration becomes necessary when data comes from multiple machines or modules, and in every other situation where more than one table is required. It is especially important because manufacturing companies rarely operate a single machine; they usually manage an entire machine fleet. This process requires as much attention as the previous stages. A simple table join on one key is often insufficient. During model development, reporting data frequently needs to be mapped to individual manufacturing stages, requiring a more complex data-modeling process.
Secure, efficient storage and access to data
Projects of this type often need a solution for affordable, high-performance data storage. A database does more than store data: it also needs to process and provide that data quickly. We select the solution for the organization’s needs: a Snowflake data cloud, a conventional server based on technology such as Microsoft SQL Server, or a server solution included in a Business Intelligence toolset. We select the right option after examining the organization’s environment and requirements. 😊
Clear data visualization gives the team control over its processes
The final essential building block is effective data visualization that makes reports clear and understandable. Although our entire BI team values simplicity in report design, not every event recorded in the data can be presented with bars and lines. We create more inventive visualizations when needed to present important events and characteristics found in client data. We also preserve the context surrounding those events, which is often essential to showing the complete situation.
If the company needs support with collecting, modeling, or reporting manufacturing data, contact us. We will select the right solutions so the team no longer has to search endless tables for the information it needs.
