MUWO PROJECT
Project Description
Muwo aims to create an opportunity to use production systems more effectively through flexible scaling. Scalability is achieved by the development of smart hardware interfaces. This will allow workstations to advance to multi-method workstations that support both manual and automated processes. Additionally, workstations can combine different processes. A transmutable simulation validates the workstation configuration and a process combiner optimizes the production configuration using AI/ML methods. Through this, Muwo improves the design and operation of production systems.
Goals
The MUWO project will develop an AI-driven quality improvement system and deploy it at IDEPA (Portugal), Alp Aviation (Turkey), and Albero (Spain) shopfloor to match the company quality improvement objectives. As such, the MUWO platform will:
Identify the most relevant equipment parameters (ex: operating temperatures, vibration, power consumption) and/or product features that are more relevant to predict quality issues on finished product
Forecast deviations at quality level before they actually happen and provide enhanced awareness mechanisms to avoid them in a timely manner to reduce waste and increase efficiency and quality
Provide proactive suggestions for quality improvement in what concerns to equipment usage and production planning
Integrate quality with maintenance (proactively suggest maintenance/corrective/preventive actions as quality problems are prognosed)
The AI-Driven Quality Improvement System would make extensive use of real-time and historical data from the several available sources, AI methods including Data Science approaches to provide relevant feature extraction, insight discovery and advanced prognosis technology for quality improvement.
Use Cases
Idepa is a textile manufacturing company located in Portugal producing textile fine fittings with more tan 50 years of history. As part of its ambition to deliver high quality products to its customers, it aims to leverage the data acquired from four industrial legacy looms retrofitted with the latest digital sensors, edge processing technologies and protocols.
This pilot aims to develop an Equipment Health Monitoring System that will allow the visualization of data collected from the industrial loom machines located in the Jacquard Loom section and will trigger warnings, thanks to scheduling algorithms, predictive maintenance and quality prediction modules.
Established in 1998 in Eskisehir, Turkey; Alp Aviation is a privately owned company with absolute dedication to the aerospace industry and its highest standards. With its efficient operations, quality, design and lean manufacturing practices, Alp Aviation manufactures flight critical and rotating parts, systems and subsystems for various customers around the world.The main objective of the pilot is to operate the GTF Rotor cell, which produces 45 different parts with 4 CNC machines during the year, with minimum loss. Reading the production data from the factory production plan, transferring the parts to be produced by making machine capacity planning to the virtual cell, finding the optimum production result according to different variations in the virtual cell and transferring it to the real production cell are the steps of the project.
Albero is a Spanish company with a highly qualified and more than fifty year- experienced staff.Their main is the plate structures manufacturing, always focused on light boiler making products. The products manufactured belong to elevator industry such as both passenger and charging elevator components, as well as doors, elevator and garaje guide rod doors, metal coverings. At the same time , we also have to mention other industry sectors as lighting components, electrical , cooling or railway components.
The main goal of this pilot is to develop an Integrated manufacturing Platform that will offer intelligent production planning thanks to artificial intelligence algorithms capable of integrating data on ERP and WMS to propose a flexible production plan that allows increasing the efficiency of the processes, as well as monitoring production performance in the bending area.
Use Cases
Idepa is a textile manufacturing company located in Portugal producing textile fine fittings with more tan 50 years of history. As part of its ambition to deliver high quality products to its customers, it aims to leverage the data acquired from four industrial legacy looms retrofitted with the latest digital sensors, edge processing technologies and protocols.
This pilot aims to develop an Equipment Health Monitoring System that will allow the visualization of data collected from the industrial loom machines located in the Jacquard Loom section and will trigger warnings, thanks to scheduling algorithms, predictive maintenance and quality prediction modules.
Established in 1998 in Eskisehir, Turkey; Alp Aviation is a privately owned company with absolute dedication to the aerospace industry and its highest standards. With its efficient operations, quality, design and lean manufacturing practices, Alp Aviation manufactures flight critical and rotating parts, systems and subsystems for various customers around the world.The main objective of the pilot is to operate the GTF Rotor cell, which produces 45 different parts with 4 CNC machines during the year, with minimum loss. Reading the production data from the factory production plan, transferring the parts to be produced by making machine capacity planning to the virtual cell, finding the optimum production result according to different variations in the virtual cell and transferring it to the real production cell are the steps of the project.
Albero is a Spanish company with a highly qualified and more than fifty year- experienced staff.Their main is the plate structures manufacturing, always focused on light boiler making products. The products manufactured belong to elevator industry such as both passenger and charging elevator components, as well as doors, elevator and garaje guide rod doors, metal coverings. At the same time , we also have to mention other industry sectors as lighting components, electrical , cooling or railway components.
The main goal of this pilot is to develop an Integrated manufacturing Platform that will offer intelligent production planning thanks to artificial intelligence algorithms capable of integrating data on ERP and WMS to propose a flexible production plan that allows increasing the efficiency of the processes, as well as monitoring production performance in the bending area.