Plataine
Canvas Category Software : Operational Technology : IIoT
Plataine is an award-winning leading provider of Intelligent Automation and Optimization software solutions for advanced manufacturing. Plataine’s solutions provide intelligent, connected Digital Assistants for production floor management and staff, empowering manufacturers to make optimized decisions in real-time, every time. Plataine is the leading provider of Industrial IoT and AI-based optimization solutions for advanced manufacturing. Plataine’s intelligent, connected Digital Assistants take manufacturing to the next level by automating and optimizing decision flows on the production floor. Combining state-of-the-art AI with extensive manufacturing knowledge, Plataine’s cloud-based solutions continually assess current status and predict future events on the production floor, to provide actionable insights, alerts and recommendations, empowering production management and staff to make optimized decisions in real-time, every time. Plataine enables global manufacturers to drive digital transformation and further increase the business value they generate from our offerings. Plataine’s patent-protected technologies are used by leading manufacturers worldwide, including Airbus, GE, IAI, Triumph, Stelia North America, Alestis, Enercon, TPI, Kineco-Kaman, IFS, Light & Strong and Ethan Allen. Plataine partners with SAP, Siemens PLM the Advanced Manufacturing Research Centre (AMRC) with Boeing, and CTC GmbH (an Airbus Company), and is also a part of the UK National Composites Centre (NCC) membership network, to advance the ‘Factory of the Future’ worldwide.
Assembly Line
Plataine Unveils AI-Based Autoclave Scheduling Optimization Solution
Plataine, a leading innovator of AI-based manufacturing optimization solutions, introduces its Autoclave Scheduler Solution, part of Plataine’s Total Production Optimization (TPO) solution suite. Operating autoclaves is associated with significant expenses, a high carbon footprint, and often creating a bottleneck in production processes. The complexity of handling multiple recipes, part & machine profiles, and designated tools has historically led to inefficient utilization, with autoclaves running well below capacity.
Plataine’s AI-driven Autoclave Scheduler optimizes autoclave operations, considering real-time production factors, such as autoclave volume and capacity, part recipes, vacuum-port & daisy-chaining restrictions and considerations, digital management of physical assets (Tokenization), tool variations, human capacity, shifts and availability, and the overall production situation up- and down-stream from the autoclaves to automatically generate optimized and practical plans. The plans adhere to all restrictions, requirements, capacities, and availabilities of relevant resources and demand sets. They follow business rules, machine profiles and material recipes and priorities, ensuring due dates are met while optimizing each autoclave run to its fullest potential.
Plant tour: Middle River Aerostructure Systems, Baltimore, Md., U.S.
Current production programs at MRAS include the LEAP-1A engine for the Airbus A320neo, LEAP-1C for the Comac C919, the CF-6 engine for multiple civil and military widebody aircraft, the Passport 20 engine for Bombardier’s Global 7500 business jet, the CF34-10A engine for the Comac ARJ21 and the GE9X engine for the Boeing 777X.
“For us, it was the integration with engineering, ERP and MRP that was key,” says Diederich. “Plataine integrates into all of this. It manages the raw materials coming in, generates cut plans per our engineering and marks the labels on the kit plies. We can dynamically nest up to 10 parts. The Plataine software uses AI to recommend which rolls of raw material should be cut next.” What is dynamic nesting? “Optimizing the nests on the fly as the software receives new inputs or when we query it,” says Diederich. “It can also send us alarms to change materials or operations. The sorted ply information is output to the Eastman systems, which have “cut and collect” software that identifies plies for kits using different colored lights. These match stacking tables at the conveyor’s end. ”
How to supercharge manufacturing yield and efficiency
Traditional nesting software has reached the limits of the efficiencies it can deliver at the product level. Manufacturers focused on continuous improvement of their production processes are now turning to more accurate metrics and a holistic approach to reduce additional waste in the nesting and cutting process.
The problem with focusing only on product level nesting yield (the total area of the parts in a product divided by the area of the material used for the nest) is that it can give an illusion of a higher yield in production. Whereas by measuring overall manufacturing yield, manufacturing companies can improve their actual overall material utilization, especially in manufacturing sites that produce multiple parts and quantities for their customers. Identifying inefficiencies in production, such as piling up and eventually discarding material remnants and short rolls, allows manufacturers to employ production optimization software to address previously hidden problems and create dynamic nests on the fly.
Sustainability in Aerospace Composites Manufacturing: How AI and IIoT Drive Results
The U.S. Environmental Protection Agency defines sustainable manufacturing as the creation of products in a manner that takes environmental factors into consideration and actively seeks to minimize negative impacts while saving on energy and natural resources. Sustainable manufacturing also enhances employee, community and product safety. Naturally, AI and IIoT are leveraged in the composite manufacturing industry in order to enhance material savings, reduce waste and increase throughput while minimizing energy consumption.
A step-by-step journey: How this Aerospace composites factory optimizes production with AI & IIoT
The powerful combination of IIot and advanced AI that smoothly integrate with existing software (ERP or MES) enable the benefits described above. IIoT sensors automatically track important real-time factors such as location, status, temperature and time. The sensor data collected is consumed by advanced applications (Digital Assistants) using AI algorithms that consider the present context, including upcoming demand and plans, providing actionable insights and recommendations in real time around critical areas such as material expiration, autoclave throughput, production demand, delivery deadlines, supply chain issues, etc.
Smart Factories and the Current State of Industry 4.0
These Alarming signs show that your Manufacturing ERP or MES is stagnating the business
MES and Manufacturing ERP systems defined the paperless transition of the last two decades. These disruptive technologies were used to collate and aggregate manufacturing data to streamline manufacturing processes. MES solved and still solves crucial challenges such as managing complex data and taking advantage of data analytics.
MES and ERP without AI and extreme automation capabilities means they lack the ability to respond to what really happens on your factory floor and have become one-dimensional legacy solutions in a multi-dimensional context where automating workflows and data-driven insights are essential to cost reduction and profit optimization.