LLumin’s CEO presents at annual PMMI conference

Recently, LLumin’s CEO, Ed Garibian, presented at the PMMI Annual Meeting in Detroit. Ed focused his presentation on the value of reducing downtime across facilities. Speaking to PMMI’s audience, he discussed how OEMs can integrate learnings from machine data into a machine-as-a-service strategy. This article briefly recaps Ed’s presentation.


Recapping how LLumin established itself

LLumin is an enterprise CMMS, asset management, and materials management software solution. LLumin uses machine data to create well-thought-out, predictive products for operations. The purpose of LLumin’s product for OEMs is to improve machine performance, maintain ongoing customer relationships, recurring revenue models, and a bridge to a MAAS (Machine as a service) model.


The Core Four Features

Four key features help companies achieve successful asset management. These include staging content, smart maintenance, operator insight, and remote monitoring. 

  1. Staging Content: Produce and stage content for consumers, such as training content, augmented reality experiences to the machine platform.
  2. Smart Maintenance: Machine condition and analytics used to facilitate the prediction of when machines need maintenance.
  3. Operator Insight: Communicating over time with the machine operator and transferring relevant information about the machine to inform maintenance decisions.
  4. Remote Monitoring: Monitor the operation of machines and performance analytics over time from anywhere (meaning management can access the information regardless of if they are on-site). This will provide access to all of the machines, along with their services, progress, and statuses.


The Value of LLumin for OEMs

With LLumin’s software, it’s easier to track machines, predict and solve future maintenance issues. Not to mention, the data OEMs can track provides invaluable information about maintenance and machine manufacturing. It also helps customers operate facilities and reduce their downtime. Technology like this helps team members work more efficiently. Maintenance is no longer reactive, but predictive.