Uptimo

An AI brain for metal AM manufacturers that tracks and maximizes production performance.

Uptimo is a predictive performance application that delivers data-driven decisions to save you time and money. Its set of proprietary algorithms analyze your production providing continuous feedback about AM systems and operations.

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Discover Uptimo

2.5x capacity
while maintaining current equipment

Uptimo delivers valuable production performance insights to drive informative decisions on daily operations, periodical reviews, and long-term strategy.

While supporting metal AM companies, we have developed industry-specific algorithms that evaluate the planning and performance of machines to reveal where time and capacity are underutilized.

This helps you make decisions on what production bottlenecks to focus on, including machine planning, build layout and parameter optimization, as well as any aspect of the metal AM process that impacts the costs and quality of the final product.

By eliminating these wastes, Uptimo maximizes the capacity of existing systems saving you investment costs on additional equipment.

Uptimo improves day-to-day operations in every step of the additive production process to deliver maximum productivity. Both AM project managers and machine operators can benefit from key features that make their daily tasks agile and painless:

Resource and machine task management

Uptimo delivers key data to the right person at the right time throughout the production process.  Information such as what build is coming up next, the powder type and amount to be used or the QC steps to be performed no longer need to be searched for.

Efficiency-based scheduling

Uptimo schedules the ideal machine pipeline that ensures the least amount of downtime, based on the resources available. Automated, efficiency-based pipelines allow your team to save precious time and make sure downtime is minimized.

Powder traceability

Uptimo tracks all powder related data throughout the powder’s entire life cycle. Every event and transformation affecting powder is recorded and used to deliver valuable insights on powder and build output performance.

Individual build optimization

Uptimo provides Project Managers with all necessary data to optimize parts and parameters at a build level prior to production, so that you can be sure to build 100% efficiently from the start.

Uptimo allows your team to review their performance in a period-over-period fashion, visualizing and prioritizing production wastes as well as their trend over time. Moreover, uptimo’s Review analytics enable a deep dive into each type of loss through the following features:

Part performance and machine calibration tracking

Uptimo inspects the correlation among part performance, laser degradation and systems fine-tuning calibration to identify and avoid entering any range of likely output failure.

Production performance insights

Uptimo displays insights on the past performance identifying trends across materials, machines, part size and part complexity, allowing the team to identify mistakes and areas that need improvement, learn on an ongoing basis, establish goals and track their growth over time.

Cost analysis

Uptimo tracks the costs from the entire production ecosystem – machines, materials, people and consumables – to allowing you to quantify not only the production wastes, but also what wastes have a higher impact on the revenue.

Failure analysis

Based on Supervised Machine Learning, Uptimo’s FMEA feature allows you to deep dive into the root cause of production failures and defines best practices to avoid repeating them.

Uptimo’s goal is to drive AM manufacturers towards a successful path by enabling faster and more informed decision-making. This module is designed for Production Managers and CFOs to give transparency on how operations’ efficiency directly impacts revenue:

True production cost

For any period of time, Uptimo determines the true costs of production down to the voxel and ties them to the costs initially forecasted as well as the ROI. This allows a comprehensive financial analysis, supporting the improvement of future performance and budgetary forecasts.

TEEP analysis

Uptimo measures the entire factory Total Effective Equipment Performance as well as the individual performance of each system for any given period of time. Such analysis gives you the big picture you are missing on the performance of your additive business over time.

Profitable market niche

WIth Uptimo, you can discover where the strengths of your production lie. By analyzing your historical performance across industry, material, geometry size and complexity, you can identify the perfect market and product niche that your business should be targeting or dropping.

Uptimo aims to drive waste reduction practices to all OEMs and part manufacturers in the Additive industry. By measuring the entire process performance of AM machines and revealing operational wastes, Uptimo can help reducing output rejections, waste materials, and carbon emissions:

Reframing performance in financial terms

By quantifying the factory performance in monetary terms, Uptimo shows how operations are directly connected to waste and therefore to financial losses.

Join the leaders in the AM community by complying with Environmental, Social and Governance (ESG) best practices, setting an example for the future of AM. If everyone in your organization can openly see production wastes that occur on a daily basis, they will likely be more inclined in supporting optimizations aimed at improving sustainability.

With Uptimo, you will improve your operational performance and save
  • Energy use
  • Material waste
  • Quality control at 3x the production cost

With uptimo, intuition no longer plays a role in weekly meetings; every outcome of the process is synthesized and visualized in a way that allows you to make quick and informed decisions.

Matthew GarrettCOO of I3D

Uptimo enables us to identify all production wastes and bottlenecks, tells us what we must focus on next to improve performance and shows how operations impact the ROI. We can finally achieve continuous improvement in AM.

Charles De ForgesCEO of Spartacus 3D
Market Advantage
Software Integrations
Hardware Compatibility
Software Deployment
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1. Build metadata gets uploaded to Uptimo.
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2. Build consumables are allocated for production.
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3. Build parameters and schedule are optimized before commencing production.
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4. All operations the build undergoes as well as any resources utilized are tracked in the software (consumables, machine, build, powder, team).
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5. Performance of builds, machines & factory resources is automatically analyzed by the software and ready for review.

Operational Excellence in AM

In order to provide high level analytics and oversight across the entire additive chain, Uptimo is designed around Operational Excellence principles. Operational excellence is widely used in advanced manufacturing, but never in AM companies due to the complexity, specificity, and constant evolution of production processes, until now.

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 project basis, or system basis over a defined time period. Additionally, there are metrics that reveal machine performance based on organizational-level workflow, and on components such as machine preparation, scheduling, parameter productivity, support volume, etc. These components contribute to making the highest quality additive part in the shortest amount of time.

Production waste management

Uptimo makes suggestions on how to improve your production process by analysing the waste identified in the production chain by waste type. Information is used to determine where resources should be allocated and the financial and time benefits this will provide to your organization. These insights provide users with control of their operations and oversight into any aspect of the production chain that may go wrong on a continuous basis.

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