Improve your metal 3D printing process performance
Thanks to Uptimo’s unique Key Performance Indicators (KPIs), it is simple to identify where and how waste is being created, define preventative measures and train the organization towards reaching optimal performance. This solution promises a significant increase in profits as well as a reduction in wastes through a unique software package that offers the following benefits:
→ Fully customized solution
→ Defines inefficiencies for a hierarchical waste management
→ Maximizes machine utilization and process efficiency
→ Metrics comparison between projects, independent of specific machine, materials and applications
→ KPIs tailored for the AM industry
→ Support in the decision making process on the final pricing of goods
→ Dynamic improvement in procedures and reduction of failures
Operational Excellence specifically made for the Additive world
In order to provide high level analytics and oversight across the entire additive chain, Uptimo is designed around Operational Excellence principles. Operational excellence tools and techniques are widely used in advanced manufacturing, but hardly in AM companies due to the complexity, specificity, and constant evolution of production processes, until now. Magnitude’s product makes it possible to reach the efficiency of lean manufacturing even in the complex world of Additive Manufacturing through two main features:
Predictive project performance
The main features of Uptimo are the predictive performance metrics of AMI, Planning, Parameters and Parts. The AM Index, or AMI, is an indicator of machine-specific performance on an individual project basis, or to monitor the systems over a defined time period, in order to reveal the level at which they are performing. Additionally, there are metrics that reveal how the machine is performing based on the organizational-level workflow, as well as individual components that make an additive part of the highest quality in the shortest amount of time, such as machine preparation, scheduling, parameter productivity, support volume, etc.
Smart resource allocation
Besides for quantifying the AM production practices, Uptimo makes suggestions on how to improve them through the wastes identified in the manufacturing chain. This information is used to determine where resources should be allocated and the concrete benefits, financially or in terms of time savings, this will provide to an organization. Combined, these insights provide users with control of their operations and oversight into any aspect of the production chain that may go wrong in subsequent projects.