AI Tool from SPIE AUTOMATION Boosts Productivity at Ifm

AI tool from sPIE AUTOMATION boosts the PRoductivity of ifm's AMR fleet

E.RAMP is a fleet analysis and monitoring tool. It provides robotics systems with maximum efficiency and optimal utilization. The productive rollout at ifm took place in mid-2022.

Challenge and Objective

A company is only as good as its employees – and these are now no longer exclusively human. The automation and digital technology manufacturer ifm has been relying on an autonomous, mobile robot fleet for quite some time. To optimize their utilization and increase productivity, SPIE AUTOMATION developed the monitoring and analysis tool E.RAMP. It collects, visualizes, and analyzes data from an AGV fleet, such as the runtime of a mission.

Solution

In June 2021, a simple data collector was initially implemented to record and review robot data. For initial visualization, the open-source application Grafana was used. It quickly became clear: pure monitoring leaves a lot of potential untapped.

Therefore, E.RAMP now offers additional analysis options:

From the recorded data, movement profiles, ERROR or waiting hotspots are displayed on uploaded maps – also in relation to different times of day.
Furthermore, individual missions can be replayed on the map to detect collisions or errors. This way, productivity potentials are quickly identified and utilized.
Analyses can be performed for individual periods at the fleet or individual robot level.
Due to ever-increasing data volumes and resulting longer analysis jobs, a queuing mechanism was implemented. This way, the portal user always has an overview of which analysis requests they have already created.

The development of E.RAMP began in August 2021, and the first version was presented to ifm’s production management as early as October 2021. To stay close to its partner’s needs, SPIE AUTOMATION designed the development process to be agile. The look & feel and the feature offering were continuously improved, implemented in MVPs, and presented to ifm.

Benefits

Cloud-based data management allows new software versions and patches to be rolled out automatically. The lean infrastructure can be scaled more easily with increasing data volumes to save on local operating costs. There were concerns regarding data security. However, SPIE AUTOMATION has extensive experience in the retail sector, including experts in personal data processing. Through detailed and transparent discussions, SPIE AUTOMATION was able to demonstrate to ifm’s IT security that E.RAMP secures all data according to the highest standards. Nothing stood in the way of the project’s continued joint development.

E.RAMP was conceptualized based on ifm’s robot fleet from Mobile Industrial Robots. However, thanks to its software architecture, E.RAMP can be used not only by other AGV users but also by other AGV manufacturers. The data collector is individually customizable for this purpose.

E.RAMP is the solution for comprehensive fleet management. It provides robotics systems with maximum efficiency and optimal utilization. The productive rollout at ifm took place in mid-2022.

About our customer
Measure, control, regulate – when it comes to pioneering automation technology, the ifm group of companies is the ideal partner. Since its founding in 1969, ifm has been developing, producing, and distributing sensors, controls, and systems for industrial automation worldwide. Today, the second-generation family-run ifm group of companies, with more than 8,000 employees in 95 countries, is one of the global industry leaders. As a medium-sized group, ifm combines the internationality and innovative strength of a growing group of companies with the flexibility and customer proximity of a medium-sized business.

Industry
Automation and Sensor Technology

Thanks to the close and collaborative cooperation in the development of E.RAMP, hurdles were quickly overcome, and there was ongoing adaptation to our needs. E.RAMP stands out for us as an important analysis and monitoring tool. It enables precise determination of AGV routes and mission sequences, based on historical data. In the future, these will be used for both error management and utilization and capacity planning.

Andreas Rist
Purchasing Investments / MRO
Ifm

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