Data Management

Data ManagementFrom Signal.X’s inception we have learned how to apply universal concepts of data management, metric-based design, data reuse, and process improvement to the plant floor. Our focus has been on implementing practical, pragmatic methods and technologies that benefit the plant. Even if we didn’t use the buzzwords in the beginning, these technologies are based on the concepts of IIoT, Smart Manufacturing, and Industry 4.0. How can factories dip their toes in the water of these concepts while producing quality parts and overcoming the challenges they represent? In the area of manufacturing test, we believe this fundamentally is about managing the flow of information, the reuse of datasets, and “closing the loop” with your manufacturing process.

Managing Information Flow

Making data from the plant floor test machines accessible to the wider community primarily involves networking computing elements together and bringing data into a common database. However, if your data is not standardized, this exercise can be very difficult or labor-intensive. Factories have to approach manufacturing test systems with an eye toward standardizing how data is collected and how results are stored. This is the first step in being able to reuse it later on.

Reusing Datasets

Once the data is stored and accessible, you can start to reuse it by processing that historical data in new ways to get new insights. To do this, you need a way to analyze data offline followed by a way to batch process that data using a new processing instruction.

Closing the Loop

The investment to create big standardized data sets is amplified many times over when data is routinely reused to explore issues of design, keep pace with development, and to improve the manufacturing process. When the answer resides in the data history, engineers need a platform to extract, study, and report on those answers. Those insights can then be used to alter the test, tighten limits, and monitor for production issues upstream.

These three items can’t be accomplished in isolation. Rather, they require an ecosystem of tools designed with this mission from the outset. If done properly, new manufacturing test systems can become a key aspect of leveraging new technologies to improve productivity and quality at your facility. Our vision is that a production test engineer has the data and insights at his or her fingertips not just to keep machines running, but to drive process and product improvements based on the knowledge from our suite of tools for control, collection, and collaboration. This can serve to integrate the assembly and test areas of the factory, maximizing productivity and quality while minimizing downtime and rework.

Data Management

Data ManagementFrom Signal.X’s inception we have learned how to apply universal concepts of data management, metric-based design, data reuse, and process improvement to the plant floor. Our focus has been on implementing practical, pragmatic methods and technologies that benefit the plant. Even if we didn’t use the buzzwords in the beginning, these technologies are based on the concepts of IIoT, Smart Manufacturing, and Industry 4.0. How can factories dip their toes in the water of these concepts while producing quality parts and overcoming the challenges they represent? In the area of manufacturing test, we believe this fundamentally is about managing the flow of information, the reuse of datasets, and “closing the loop” with your manufacturing process.

Managing Information Flow

Making data from the plant floor test machines accessible to the wider community primarily involves networking computing elements together and bringing data into a common database. However, if your data is not standardized, this exercise can be very difficult or labor-intensive. Factories have to approach manufacturing test systems with an eye toward standardizing how data is collected and how results are stored. This is the first step in being able to reuse it later on.

Reusing Datasets

Once the data is stored and accessible, you can start to reuse it by processing that historical data in new ways to get new insights. To do this, you need a way to analyze data offline followed by a way to batch process that data using a new processing instruction.

Closing the Loop

The investment to create big standardized data sets is amplified many times over when data is routinely reused to explore issues of design, keep pace with development, and to improve the manufacturing process. When the answer resides in the data history, engineers need a platform to extract, study, and report on those answers. Those insights can then be used to alter the test, tighten limits, and monitor for production issues upstream.

These three items can’t be accomplished in isolation. Rather, they require an ecosystem of tools designed with this mission from the outset. If done properly, new manufacturing test systems can become a key aspect of leveraging new technologies to improve productivity and quality at your facility. Our vision is that a production test engineer has the data and insights at his or her fingertips not just to keep machines running, but to drive process and product improvements based on the knowledge from our suite of tools for control, collection, and collaboration. This can serve to integrate the assembly and test areas of the factory, maximizing productivity and quality while minimizing downtime and rework.

CONNECT WITH US

YouTubeLinkedInNational InstrumentsControl System Integrators Association

CONNECT WITH US

YouTubeLinkedInNational InstrumentsControl System Integrators Association