Gal Garniek, President & CEO
Industry 4.0 is transforming the way manufacturing organizations work; however, there is a big gap in moving to industry 4.0 and harnessing its big data and predictive analytics advantages for the purpose of optimizing overall equipment effectiveness (OEE) through real-time machine data. Access to such data and analyzing it to gain meaningful insights to optimize OEE has been a great challenge for manufacturers. Coupled with this, the capital and operational costs of upgrading and switching from legacy to new machines is also a significant hurdle in the industry, leaving many manufacturers exposed to managing potentially significant costs without the right insights and tools.
GEM, a California-based company designed its cloud-based Precare IIoT platform to mitigate these challenges, enabling manufacturers to migrate and upgrade industrial systems efficiently and cost-effectively while harnessing the complete benefits of smart factory automation in terms of mission-critical KPIs, such as OEE, Availability, Performance, Quality, MTBF and MTBA, coupled with the ability to know when exactly to schedule equipment maintenance (predictive maintenance or PdM). “Our ultimate mission is to create world‐class products and services that provide enterprises and users with mission-critical data, insights, and decision-making tools through the use of IoT and Machine Learning,” begins Gal Garniek, President & CEO of GEM.
Having worked in the network and data infrastructure space for more than two decades, Garniek notes, “The KPIs are extremely useful in understanding how the problems in manufacturing lines negatively affect machine availability, performance and output quality.” GEM is dedicated to improving the experience, productivity, quality, and overall equipment effectiveness of manufacturing enterprises by means of a platform that tightly couples data acquisition with big data analytics and predictive analytics, enabling them to provide a complete, cost-effective smart manufacturing migration solution.
GEM’s Precare platform has the capability of adding Industry 4.0 data acquisition and predictive analytics to any factory floor within 24 hours of engagement. With this real‐time data acquisition ability, compiling mission-critical KPIs and optimization insights from the factory floors are no longer a prohibitive cost factor for manufacturers. “Our core strength lies in the ability to create scalable frameworks around the extraction of mission-critical data from any machine and analyzing them,” states Garniek. Through this, GEM provides manufacturers the opportunity for additional margin and revenue growth in their manufacturing operations.
From a financial standpoint, GEM offers capital expenditure (CAPEX) and operational expenditure (OPEX) savings. The company’s real-time data acquisition off legacy machines prevents the CAPEX for new machines, while the transparent connectivity and no operational training requirement cuts down the OPEX.
GEM offers six key Precare products—Edge, Cloud, KPIs, Predictive maintenance (PdM), Dashboards, and Reports—on its platform. Precare Edge facilitates digital twin representations of machines, data acquisition, complex edge processing, machine vision, and predictive analytics at the edge.
Rich technology stacks, Unique Edge, Data Integration and Analytics IP, agility and consistently high level of service to our customers and partners allow us to organically expand within existing customer accounts and address new customer opportunities
GEM’s Precare Cloud facilitates data storage, retrieval of machine data, machine learning, and computation of KPIs, while the Precare KPIs product provides real-time insight into OEE, Availability, Performance, Quality, MTBF, and MTBA with drill‐down from the corporate level to the machine. Rolled-up KPIs provide C‐suite executives with real‐time corporate level insights, while KPIs at the factory floor, machine, and event levels provide managers, operators, and engineering with real‐time insights down to the most detailed level of the equipment.
GEM’s Precare PdM deploys sophisticated machine learning algorithms, and automated machine learning process flows to predict with high accuracy when a machine failure will occur, allowing manufacturers to schedule just-in-time maintenance in order to reduce machine downtime and optimize equipment performance and output quality. GEM’s Precare Dashboard provides a clear and functional presentation of statuses, alarms, trends, KPIs, while Precare Reports provides standard and custom formatted data with extensive sets of filters and can be scheduled to run automatically.
Testimony to the benefits of the GEM Precare IIoT platform is the case of a large semiconductor manufacturer that lacked visibility into mission-critical KPIs at every level of its manufacturing operations. The enormous CAPEX and OPEX for upgrading to newer equipment were simply not justified. The deployment of GEM Precare agents resulted in digital twins for the factory machines, facilitating the acquisition of real-time data from the machines. This data fed GEM Precare KPIs resulting in real-time OEE, Availability, Performance, Quality, MTBF, and MTBA KPIs displayed for the manufacturer at any level of its operations, all the way down to machine events; all this within 24 hours of engagement.
As a result, the manufacturer gained 100 percent visibility into real-time KPI data and 20 percent increase in machine availability, resulting in a positive impact on gross margins and revenue, without the large CAPEX and OPEX associated with purchasing and deploying Industry 4.0 ready machines. Return on investment was a matter of a few months from the time of deployment. Consequently, the customer continues to expand the GEM Precare footprint within its manufacturing operations.
GEM offers its Precare IIoT platform across various sectors, among which the semiconductor and electronics manufacturing industries are at the core of the company’s business. These industries serve multi-billion markets, such as automotive, computing, telecom, datacom, and consumer markets. The experience gained from the semiconductor manufacturing industry, and tools developed for KPIs are highly transferrable to other industries; hence, GEM’s next growth step is to expand into industries of electronics, plastics, and heavy manufacturing. Augmenting any machine with automatic data collection is what makes GEM stand out from its competitors. “By delivering rich technology stacks, agility, and consistently high levels of service to our customers and partners allows us to organically expand within existing customer accounts and address new customer opportunities,” concludes Garniek.