Artificial Intelligence in Manufacturing

The company has designed Deep Learning Inference Accelerator (DLIA), integrated hardware, software frameworks, and libraries such as Intel Math Kernel Library for Deep Neural Networks (MKL-DNN) and Caffe, which simplifies the neural-network acceleration for image processing applications.

NVIDIA Corporation is one of the leading providers of deep learning hardware. The company also provides AI platforms, which is used in manufacturing plant. NVIDIA Corporation has designed an AI supercomputer—NVIDIA DGX Station for easy experimentation at the office, lab, or workspace. This integrated hardware and software solution helps the user to research more on deep learning for various purposes in manufacturing. This solution reduces both the expenditure and time, as well as has a computing capacity of four server racks. In addition the company’s continuous technological advancements have resulted in its very high rating.

IBM Watson’s Intelligent Asset and Equipment Solutions improves the reliability and performance of machines in the manufacturing plant through better visibility, predictability, and operational efficiency. IBM Plant Performance Analytics predicts equipment failure, prescribes remedial procedures, and optimizes maintenance schedules to minimize the impact on the overall equipment effectiveness. IBM Prescriptive Maintenance on Cloud gets a prediction of machine performance issues, percentage probabilities of occurrence, probable time to occurrence, probable time to recover, and root causes.

Google Cloud Machine Learning Engine, part of Google’s AI platform, is a managed service that enables engineers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.

GE Predix platform is used for Industrial IoT app development purpose. This is divided into three segments—Edge Connectivity and Insight, Cloud Application Services, and Apps Visibility and Insight. The Edge Connectivity and Insight connect the assets, gateways, controller, sensors with Edge Analytics, whereas the Cloud Application Services provide Digital Twin Modeling and Analytics Platform. The Predix Apps is an industrial intelligence dashboard, which provides prediction analysis and conditions of assets, operations, and business. The company’s digital twin solution provides a wide range of solutions for predictive maintenance and machinery inspection in the manufacturing sector.

Microsoft AI technology provides the intelligence to see, hear, recognize faces, detect emotions, interpret language, infer intent, and prescribe and automate outcomes.Microsoft Corporation has a moderate number of products in the AI in manufacturing market.

Siemens AG offers Intelligent Data Analysis, a machine learning technology that is used to optimize industrial facilities. This technology is also used in energy distribution, electric motors, and rail technology. Moreover, the company’s AI-based technology improves the operation of wind turbines by adjusting the position of the rotors to change the direction of the wind to get the highest amount of yield from a wind farm. The company’s industrial operating system “MindSphere” provides intelligent data analysis with regard to predictive maintenance.

DataRPM Cognitive Anomaly Detection and Prediction (CADP) is a comprehensive solution for achieving asset failure management that helps to enhance overall productivity. It uses meta-learning technology to automate predictions of asset failures. This ensures users to leverage the deluge of data generated by their machines to gain accurate insights into predicting asset breakdowns. Also, field technicians can take well-informed and proactive decisions to ensure minimal disruptions on the production floor. All this is possible by automating cognitive predictive maintenance, a process that is beyond human management.

The company offers neural network chips such as NeuroMem CM1K Chip, Intel Curie, BrainCard, CurieNeurons, and NeuroStack. This is utilized for machine learning and voice/recognition applications in AI software for manufacturing. It also provides hardware for faster calculations, which is required for deep learning technology.

The Sight Machine Platform is used for various application in the manufacturing industry, which includes machinery inspection, prediction maintenance, and field service. Moreover, this platform provides customized solutions, which indicates high scalability, thereby resulting in the company’s high rating for overall product strategies.

Skymind provides AI platform that enables data scientists and IT teams to quickly prototype, deploy, maintain, and retrain machine learning workflows that accelerate time to value. Skymind bridges the gap between data science, DevOps and the big data stack. It is an ML platform that directs engineers and data scientists through the complete workflow of building and deploying machine learning models for enterprise applications on JVM infrastructure. It can be installed on any environment: cloud, on-premises, bare-metal, or hybrid systems.

The snickerdoodle platform by KRTL, offers flexibility and optimized power and speed. It uses the Xilinx Zynq®-7000 SoC combining the ARM ecosystem with the reconfigurability of an FPGA. It offers hardware, software, and engineering solutions to mission-, safety-, and business-critical problems with core competencies in the areas of embedded systems, robotics and automation, wireless and wired communications, audio/video processing, and computer vision.

AIBrain has developed a reasoning engine called Adaptive Interactive Cognitive Reasoning Engine (AICoRE). AICoRE fully automates the end-to-end reasoning process; from sensing, reasoning, discovering, planning, learning, remembering, and responding to performing different manufacturing processes—such as machine inspection, material movement, and predictive analysis. AIBrain also offers Cognitive Multi-Agent Planner (CMAP), a solution that deals with real-world problems while interacting with multiple humans. Furthermore, AIBrain provides personal robots and conversational AI assistants in the AI in manufacturing market. For developers, AIBrain has created an intelligent robot-building software named Intelligent Robot Software Platform (IRSP).

Oracle offers its Adaptive Intelligent Applications for Manufacturing solution as a part of its artificial intelligence (AI) cloud portfolio. These applications enable manufacturers to detect anomalies during production, analyze the root cause of events, and predict issues before they occur. Manufacturers can use this solution to examine every stage of production, foresee faulty elements and processes, and track the impact of events—from production to customer delivery.

Rockwell Automation’s new AI module is designed for smart manufacturing and Industry 4.0. Using this module, industrial workers leverage the data generated by their equipment to improve processes and predict production issues with their current automation and control skillset. Rockwell’s new FactoryTalk Analytics LogixAI module, previously known as Project Sherlock, uses AI to detect production anomalies. It then alerts workers to investigate or intervene, as necessary.

SAP SE has developed an AI-based on-premise analytics solution known as ‘SAP HANA,’ which is an in-memory data platform that delivers business intelligence, accelerates business processes, and simplifies the factory automation environment. The company also offers ‘SAP Leonardo,’ a cutting-edge solution that integrates IoT, machine learning, and analytics. SAP’s AI portfolio allows manufacturers to adopt new capabilities and business models rapidly.