Canvas Category Software : Operational Technology : IIoT
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Intel embraces SDN to modernize its chip factories
The US chip giant has implemented software-defined networking in its semiconductor manufacturing plants, moving the tech beyond the data center and into a vertical seeking to benefit from zero-downtime machine connectivity. But as part of Intel’s expansive plans to upgrade and build a new generation of chip factories in line with its Integrated Device Manufacturing (IDM) 2.0 blueprint, unveiled in 2021, the Santa Clara, Calif.-based semiconductor giant opted to implement SDN within its chip-making facilities for the scalability, availability, and security benefits it delivers.
Aside from zero downtime, moving to Cisco’s Application Centric Infrastructure (ACI) enabled Intel to solve the increasingly complex security challenges associated with new forms of connectivity, ongoing threats, and software vulnerabilities. The two companies met for more than a year to plan and implement for Intel’s manufacturing process security and automation technology that had been used only in data centers. The collaboration with Cisco enables ACI to be deployed for factory floor process tools, embedded controllers, and new technologies such as IoT devices being introduced into the factory environment, according to Intel.
Intel has deployed SDN in roughly 15% of its factories to date and will continue to migrate existing Ethernet-based factories to SDN. For new implementations, Intel has chosen to use open source Ansible playbooks and scripts from GitHub to accelerate its move to SDN.
Sustainable Buildings Made Possible by Cisco and Schneider Electric
Improving asset criticality with better decision making at the plant level
The industry is beginning to see reliability, availability and maintainability (RAM) applications that integrally highlight the real constraints, including the other operational and mechanical limits. A RAM-based simulation application provides fault-tree analysis, based on actual material flows through a manufacturing process, with stage gates, inventory modeling, load sharing, standby/redundancy of equipment, operational phases, and duty cycles. In addition, a RAM application can simulate expectations of various random events such as weather, market dynamics, supply/distribution logistical events, and more. In one logistics example, a coker unit’s bottom pump was thought to be undersized and constraining the unit production. Changing the pump to a larger size did not fix the problem, because further investigation showed insufficient trucks on the train to carry the product away would not let the unit operate at full capacity.
The Power of Predictive Maintenance
“Getting to the level of predictive maintenance is an evolutionary process for manufacturers, regardless of their specialty,” notes Will Healy III, global business strategy manager at Balluff Inc. “Right now, there is great interest in retrofitting equipment with sensors to perform condition monitoring as a means to implement predictive maintenance. The next step is using equipment with integrated smart sensors and artificial intelligence. These technologies also enable prescriptive maintenance, which uses machine learning to help companies specifically adjust their operating conditions for desired production outcomes.”
One of the first robotic predictive maintenance applications of the IIoT occurred several years ago in the auto industry when General Motors teamed up with Cisco and FANUC America Corp. to launch a zero downtime program. Called ZDT, the predictive analytics service identifies potential failures so engineers and plant managers can schedule maintenance and repairs. This prevents unexpected breakdowns during production, thereby saving manufacturers time and money. According to Tuohy, the ZDT program has proven to be quite successful over the last several years. He says that about 30,000 robots worldwide are connected to the system.
Seeq Announces $50 million Series C Funding Round led by Insight Partners
Seeq Corporation, a leader in manufacturing and Industrial Internet of Things (IIoT) advanced analytics software, announced today it has closed a $50 million Series C funding round, led by global venture capital and private equity firm Insight Partners. The round includes participation from existing investors Altira Group, Chevron Technology Ventures, Cisco Investments, Saudi Aramco Energy Ventures, and Second Avenue Partners. This round brings Seeq’s total funding since inception to approximately $115 million.
Seeq’s rapid growth is being fueled in part by its partnerships and commitment to cloud-based computing. Seeq is available in the AWS Marketplace and is an AWS Industrial Competency Partner. On Azure, Seeq has been available in the Azure Marketplace since 2019 and was recently recognized as a 2020 Microsoft Energy Partner of the Year Finalist. In addition to cloud partnerships, Seeq connects to an extensive set of automation vendor data storage platforms for on premise engagements including OSIsoft, Siemens, GE, Honeywell, Emerson Automation Solutions, Inductive Automation, AVEVA, AspenTech, Yokogawa, and others.
Cisco Completes Acquisition of Fluidmesh Networks
Cisco (NASDAQ: CSCO) today announced it has completed the acquisition of Fluidmesh Networks, a leader in resilient wireless backhaul systems. Fluidmesh extends Cisco’s industrial wireless offerings to industries with on-the-move assets and mission critical applications in situations where zero data loss is critical to uptime and business resiliency.
Cisco’s scale, combined with Fluidmesh’s solution-based offerings and relationships with systems integrators, accelerates Cisco’s industrial IoT business, and enables wireless deployments within industrial envionrments. The combined offering addresses emerging use cases including remote operation of equipment and deploying autonomous robots to maximize productivity.