The "Manufacturing Analytics Control" product line is designed to analyze and optimize manufacturing performance and make predictions about future process quality. It can be deployed to complement the iTAC.MOM.Suite manufacturing operations management system, which is designed to plan, control and monitor production processes in real time; but it can also be implemented as a stand-alone solution.
"Manufacturing Analytics Control" combines software products from iTAC and its subsidiary Cogiscan. A central component is the streaming engine, which can process and link data from multiple sources in real-time, and then analyzes the performance of the entire manufacturing environment. "We are paving the way for comprehensive performance understanding. This supports operational planning, enables the identification of room for improvement and ultimately contributes to a more efficient and profitable production," explains Martin Heinz, board member of iTAC.
Providing clear insights into current and past performance, especially for critical machines and processes, the predefined key performance indicators (KPIs) allow companies to closely monitor and evaluate performance parameters. In addition, process owners can quickly identify deviations from desired setpoint and respond to them efficiently. This helps to minimize production downtime and optimize operational performance.
The ability to customize dashboards allows companies to visualize relevant KPIs and data according to their specific needs and priorities – the basis for tailored analysis and action-driven decision making. Widgets from different products can be combined in a dashboard as desired. For example, widgets for the analyses of ovens, nozzles or feeders can be selected and arranged via drag-and-drop. Another unique selling point is that machine data from upstream and downstream processes can be compared directly with each other, e.g. to run an analysis in real time. Using AI, the measurement data is correlated with the data from the AOIs (Automatic Optical Inspection) and SPIs (Solder Paste Inspection) and then mapped in a heat map.
Easy implementation and workload reduction on multiple levels
"Manufacturing Analytics Control" offers various advantages for creating added value from data and can be deployed immediately, and is a simple add-on for companies with existing infrastructure. Implementation and usage are very simple: no data scientists and no programming experience are required to get started.
The solution offers standard out-of-the-box use cases that are specifically tailored to the requirements or needs of different industries. Connectivity is ensured so that fast and straightforward connections to machines can be established: no specialized connectivity engineering team is required.
The data model has already been successfully tested in various industries. It includes comprehensive data checks, error checks, interpretations, and standardized evaluations. These functionalities serve not only to ensure quality, but also to relieve the reporting team and the data collectors.
Simplifying the tasks of data engineers by making machine data interpretable – the solution combines data from machine with necessary contextual information so that unstructured data becomes structured. Furthermore, this data is transformed into actionable workflows, with interfaces such as MS Teams to enable real-time control of actions, data and machines. It also opens the way for closed-loop control and proactive problem management. Further value can be created from the data using AI and adding AI/ML to workflows is easy.
"Companies can profit from the advantages at the push of a button, for example, quality assurance, increased overall efficiency in production, and reduced workload for employees," Martin Heinz summarizes.
