Manufacturing

From Manufacturing Automation to Intelligence

The next revolution in manufacturing will involve going beyond factory automation and into factory intelligence…from the automated factory to the predictive factory. Even in a highly automated production environment there exists intelligence gaps, both at the micro (individual asset) level and the macro (asset ecosystem) level. Closing these gaps is the next operational imperative.

Industry Challenges

Common Problems Faced by Enterprises

Shallow Observability

The absence of endpoint AI embedded and trained at the machine level restricts the ability to attain asset-specific insights and to develop predictive performance models. This creates blind spots within the manufacturing ecosystem.

Monitoring and Reporting Limitations

Machines and devices do not have the ability to self-monitor or self-report. Critical performance insights go undetected and/or unreported.

Inefficient Maintenance Procedures

Continued reliance on preventive maintenance processes that are unable to self-adjust based on current real-time conditions of the asset. This creates unnecessary downtimes and poor OEE (overall equipment effectiveness).

Legacy Knowledge Management Systems

Outdated knowledge management methodologies are unable retain and capitalize on the vast amounts of organizational knowledge produced by the enterprise. Inability to perform query-based location and retrieval of data necessary for continuous process and machine improvement.

Cyber-Security

vulnerabilities that include

Increasing digital threat surfaces provide more entry points for malicious actors.
Increased probe volume overwhelms the personnel and existing tools responsible for cyber protection.
IIoT device power/memory limitations that make them less adaptable to traditional security measures and more vulnerable to attack.
Ransomware attacks can result in the temporary or permanent loss of sensitive data. Depending on the scope of the attack, a single asset or an entire factory can be disabled.

Machine centric training

via embedded machine learning algorithms that live and learn directly on the machine asset.

Historical and predictive trend analysis

powers the transition from preventive to predictive analysis enabling development of preventive maintenance intelligence.

GenAI

that combines artificial intelligence and natural language processing (NLP) to power advancements in machine fault resolution, data retrieval, predictive analytics, resource allocation, and cost optimization.

Intelligent knowledge management

that helps manufacturers capitalize on the power of their organizational knowledge. Intelligent KMS improves overall performance and sustainability via more rapid access to critical knowledge and data.

Endpoint cyber-security

embedded directly into the manufacturing asset. Endpoint security that enables quicker detection and reaction to Zero-Day infections – staying one step ahead of hackers

Solutions

Next-Generation Capabilities for Manufacturing

Breakthrough capabilities close the gap between manufacturing automation and intelligence.

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Breaking the 70% OEE barrier

Improvements in OEE performance from the current standard of 70% to a new standard of ~ 85%. The results can be equivalent to adding a new machine or a new line of machines.

Dynamic machine health scores

Real-time, at-a-glance, assessment of performance of a single machine or an entire set of connected assets. Faster recognition and mitigation of performance issues.

Higher production levels

Predictive maintenance eliminates downtimes related to unnecessary maintenance activities and/or unforeseen malfunctions.

Enhanced cyber-security

Embedded and edge security algorithms that provide more robust cyber protection and that shorten detection and reaction times (detection in seconds instead of hours/days).

Longer asset lifespans

Real-time asset health monitoring, process-driven mitigation actions, and predictive maintenance capability all combine to extend the lifespan of capital-intensive assets.

Benefits

Benefits for Manufacturers

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Use Case

IoT Empowered Data Analytics and Dashboarding

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Take a look at how Plasma’s Solution manages 40+ million devices, and their data analytics, for one of the largest global telecom operators.

Challenge

Down to the single device level
The ability to search the immense device database
Dashboarding and Reporting capability

Solution

Data Aggregation
Analytics and Insights
Visualization Engine

Impact

Databases, API’s, devices, etc.
Optimize internal operational efficiencies
Real-time KPI information

Testimonial

What our client say about us

Our software, system and processes used to be an old struggling engine. Plasma team solved all that. With exceptional training and planning, their consultative executive team down to their support team executed the deployment with first-class speed and professionalism. Their platform not only removed all the pain points in my division, but also created a ripple effect benefiting my entire company.