Litmus Provides its Customers with an Edge

Litmus was the top ranked firm for innovation in the recent ABI Research Data Analytics in Manufacturing Competitive Ranking (CA-1266) with its ability to deliver an end-to-end analytics value chain allied with innovative user interfaces. ABI Research caught up with Litmus in November, and representatives shared information regarding a recent customer win at a multi-national food and beverage manufacturer. The customer operates plants across North America, and ensuring that clients such as Walmart receive a premium product necessitates constant monitoring of plant data. Litmus implemented an IoT platform that provides staff with immediate visualizations of their operations; data is both collected and processed at the edge as well as in the cloud for further processing.

The case provides evidence that process manufacturers are looking to edge computing to analyze and rectify their operations in real time because they have less scope than discrete manufacturers to rework defective products. Spend on data management and analytics by food, beverage, and tobacco firms is set to surpass US$1.7 billion in 2026 (see the ABI Research market data Data Management in Industrial Applications Market Tracker (MD-DMIA-101)).

Like many other manufacturers, the customer has implemented solutions from many different providers, and in so doing has several data acquisition and industrial systems in operation on the plant floor. The mix of systems meant that the customer had data residing in silos and could not perform analytics to support predictive maintenance activities nor have a coherent view of its operations.

The company implemented the Litmus Edge-to-Azure platform. First, by introducing Litmus Edge on the plant floor, all the disparate devices were connected to the platform, facilitating data collection, normalization, and analysis. In addition, the data collected is then integrated with Azure IoT Hub for further processing in the cloud. The Litmus Edge Manager provides a centralized management system for all edge deployments in the cloud, while plant visualizations and local processing on Litmus Edge is delivered via virtual machines in each plant’s data center. The analytics provided by Litmus means that the customer can create statistical models to predict machine failures, and by integrating the data into its maintenance system, can automate the creation of work orders, both reducing machine downtime and optimizing maintenance schedules.

By performing tasks at the edge of the network, mission-critical tasks can be automated thanks to data collation, processing, and analysis being performed in real time. But edge computing is a blunt instrument. Manufacturers and vendors need to design and deliver projects to solve operational problems or deliver a business outcome. Projects need to focus on shortening the time to value and not get caught in a cycle of reviewing Proof of Concepts (POCs). Litmus’s approach is to ensure it and the client agree on the criteria for success upfront and, perhaps more important, garner commitment to scale from the outset. Litmus was able to agree with the customer’s management to scale across the 35 plants after demonstrating the Litmus solution can achieve certain milestones, rather than being caught in review and reassess cycles.

Given the heterogeneity of manufacturing plants, there needs to be collaboration between OT and IT teams to facilitate data extraction and share it across the plant, agree on metrics to identify issues, and secure flexible arrangements with maintenance providers. It may be the case that further investment will be required in order to have effective communication protocols across the plant. Finally, vendors need to provide a low code/no code platform because operational teams want the sophistication of the analytics in a format that doesn’t require them to be coding experts so they can instead focus on the findings.

Litmus will be profiled in the upcoming ABI Research report Industrial Edge Hot Tech Innovators (PT-2394).