Real time analytics at the edge for manufacturing

Solving critical production & safety challenges to drive unexpected growth

Real time analytics at the edge for manufacturing Solving critical production & safety challenges to drive unexpected growth

Manufacturers &AI

Combining human experience, insight, and AI techniques, manufacturers are discovering new ways to differentiate themselves while driving down costs, protecting employees and increasing margins. Over the last 5 years, manufacturers drove massive data collection, major progress were made on the production line, however drivers of productivity (quality, time, automation, etc.) is still scarce. 95% of collected data is still waiting for appropriate treatment to generate valuable AI-originated insights. According to analysts, less than 30% of industrials actually have an AI development plan for their factory, despite over 85% of them believing they need to implement AI on their production processes.

Most IoT data are not used currently […] The dara that are used today aremostly for anomaly detection and control, not optimization and prediction, which provide the greatest value.

McKinsey

3 Key figures in themanufacturing industry

40%

99%

25%

By 2035, AI-powered technologies could increase labor productivity by up to 40% in manufacturing. (Accenture and Frontier Economics)

By 2022, 99% of video/ image content captured for enterprise purposes will be analyzed by machines rather than humans. (Deloitte)

of CEOs of large companies consider artificial intelligence as a key technology

Challenges

Predictive maintenance

87% of chief supply chain officers say it is extremely difficult to predict and manage disruptions in manufacturing supply chain management and logistics*. Many manufacturers are facing inconsistencies on the production line in the process so that issues can be corrected in real time. Risks of breakdowns slow production process and deliveries, which affect customer satisfaction and loyalty.

Objectives

• Stay in compliance with stringent regulatory requirements • Predict when machines/equipment are likely to fail and recommending optimal times to conduct maintenance • Predict potential problems and identify when specific parts need to be replaced, attaining a high level of reliability in the process.

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Solutions

Beyond minimizing downtime, computer vision solutions empowered by edge computing servers reduces maintenance costs and increases productivity. It enables manufacturers to predict issues, purchase replacement parts and plan human resources to maintain machines, without disturbing the production line.

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Challenges

Quality control

Some flaws are too subtile & too small to be detected by the human eye. Indeed, the likelihood of production errors and quality problems typically increases when dealing with a product that has many different components all varying in size and function. Manufacturers are facing strict regulatory environment to ensure consumers safety & guarantee standards of quality. In cases of non-compliant products, it can lead to significant losses from dissatisfied customers to fines and class action lawsuits.

Objectives

• Increase First Pass Yield • Decrease Rework, Crap, Recall

• Reduce cost of control • Improve On-Time Delivery

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Solutions

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On the production line, cameras scan the product in 360° simultaneously, then the edge computing server collects, processes data in real time. BullSequana Edge offering the highest inference capabilities outside the datacenter in the plant. This solution dramatically cuts the costs of real time in-line inspection are answers to these use cases:

• Machine vision inspection systems where defects get classified according to their type and are assigned an accompanying grade or default • Package Inspection : count items before placing them into containers, check for broken or partially formed packages (right

color, length, width, and whole) so defective containers are then rejected • Object identification & classification • Manufacturers can deal effectively with regulations around products spec and compliance

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Quality control process optimized by BullSequana Edge

The sorting machine receives the information from BullSequana Edge. Thus, it sorts the non-faulty parts from the defective ones.

Cameras scan products 360°

Defective product is separated

Unsorted products

Data is sent in real time to BullSequana Edge. The server can be mounted on a wall and is optimized to perform on a production line.

Challenges

Digital twin

• operational efficiency has plateaued • operators lack full visibility and control • occupants aren’t satisfied with their space • lack the ability to predict and preempt events.

Objectives

• Increased reliability of equipment and production lines • Improved OEE through reduced downtime and improved performance • Improved productivity • Reduced risk in various areas, including product availability, marketplace reputation, and more • Lower maintenance costs by predicting maintenance issues

before breakdowns occur • Faster production times

Process Digital Twin for Pharma

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Solutions

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• A digital twin is a virtual replica of a physical product, process, or system. • A digital twin acts as a bridge between the digital and physical worlds, using connected sensors and IoT devices to collect real- time data about physical items. This data is then processed within a server at the edge (BullSequana Edge or BullSequana SA) and used to understand, analyze, manipulate, and optimize the item.

The role of digital twins in producing a COVID-19 vaccine

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Digital twin

Use cases

• Using predictive maintenance to maintain equipment, production lines, and facilities • Getting a better understanding of products by monitoring them in real-time as they are used by real customers or end-users • Manufacturing process optimisation • Enhancing product traceability processes • Testing, validating, and refining assumptions • Increasing the level of integration between unconnected systems • Remote troubleshooting of equipment, regardless of geographical location

The Impact of Digital Twins on Infrastructure Maintenance

Digital twins drives industrial decarbonization

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BullSequana Edge

BullSequana SA

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Challenges

Worker safety

There are about 100 deaths per month on the job in 2019 in the USA, which has a direct impact on the company’s reputation, attractiveness, but moreover on employee’s safety feeling & productivity. It’s a high priority for manufacturers to ensure safety at all stages. The key is to ensure compliance with safety standards to prevent workplace accidents.

Objectives

• Improve compliancy to safety standards • Foster employees to respect security measures • Decrease Monthly Health and Safety Prevention Costs

Solutions

• If workers are in a hazardous and life-threatening situation • Environmental risks or hazards at the right time • Real-time abnormal situation (People on the ground..) • Dangerous driving situations with forklifts, trucks… A set of cameras is connected to BullSequana Edge servers, in case of a detection of a worker is not wearing his/her personal protective equipment (PPE) like ear plugs, helmet, gloves.. the server analyzes this information in real time and triggers an alert to production site managers. It can also detect:

How edge computing brings themost out of video analysis? Computer vision requires to process data in real time to get most value out of it. The goal of replacing traditional video analysis or human eye is to gain in precision and speed. When video data is sent to the cloud, it increases drastically the bandwidth & latency while causing privacy issues. Indeed, video data is voluminous, which can be an issue is you want to send H24 7/7 data to the cloud. It is more interesting in terms of efficiency and cost, to analyze video data at the edge close to data and then send the pre-processed data to the cloud or to the data center. Cameras captures motion Pictures are processed in the edge server

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Action is taken

AI deep learning algorithms identify people, an abnormal situation, flows etc…

Sustain your Business with Computer vision at the edge.

Edge Computer vision

About Atos BullSequana Edge server

Install anywhere • Does not need a Datacenter • Can operate in airports, shop/ factory floors, …ETSI EN 300 019 class 3.2

Data privacy P rocess critical data at its source to keep it secure No external network dependencies BullSequana Edge can communicate via radio, 4G, LTE or Wi-Fi and can thus be be fully independent from wired networks. As it is fully independent from datacenter & cloud networks connectivity, applications are not disrupted in case of limited or interrupted network connectivity. Great for streaming data ingestion / analytics Server class CPU optimized for the Edge 16 very powerful CPU cores / 32 threads

Edge optimized security • Intrusion detection • Secure Firmware update • Secure boot TPM 2.0 FIPS 140-2

Flexible Radio and NIC networking options • Cabling independent • Up to 2 Radios 4G, Wifi, Lora 1 to 10 Gbps built-in, extensible to 100Gbps

Outstanding AI acceleration capabilities • Up to 2 • Nvidia T4 GPUs Up to 2 FPGAs Powerful AI model inference for Video analytics

BullSequana Edge is multi platform certified

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Discover the video of the world’s highest performing Edge Computing server

Microsoft Azure IoT

VMware

Nvidia NGC

RHEL

Atos delivers end-to-end edge computing approach

We take into account your existing and your priorities, to go from idea to realization. The Atos approach combines business and technology expertise and accelerates the passage from idea to implementation.

Monitor and support

Deploy edge servers

Configure and Build a custom solution

Understand business stakes

Unleash the potential of your business

Contact us below mehdi.kasmi@atos.net Head of Sales, Edge & AI, Atos

Brochure

About Atos Atos is a global leader in digital transformation with 105,000 employees and annual revenue of over € 11 billion. European number one in cybersecurity, cloud and high performance computing, the Group provides tailored end-to-end solutions for all industries in 71 countries. A pioneer in decarbonization services and products, Atos is committed to a secure and decarbonized digital for its clients. Atos operates under the brands Atos and Atos|Syntel. Atos is a SE (Societas Europaea), listed on the CAC40 Paris stock index. The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

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Atos, the Atos logo, Atos|Syntel are registered trademarks of the Atos group. ©2021 Atos. Confidential information owned by Atos, to be used by the recipient only. This document, or any part of it, may not be reproduced, copied, circulated and/or distributed nor quoted without prior written approval from Atos.

CT-210319-JS-BR-Manufacturing & Computer vision

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