Better Factory Trainings
Welcome to Better Factory trainings!
This section will allow you to better understand our project, learn about our challenges and get to know RAMP Marketplace and APPS.
Our team also aims at providing the necessary training content to support the adoption of skills for deploying the Better Factory technologies and effectively implementing cyber-physical systems and collaborative robotic technologies to maximize agility in production for the personalization of products through agile manufacturing.
A final part is dedicated to non-technical learning units, e.g., business-related training, where you can find supporting content for the execution of these activities in your projects.
Onboarding to the project Better Factory
Onboarding on RAMP
RAMP (Robotics and Automation Marketplace) is a free and open IoT platform (FIWARE) running on state-of-the-art servers, with access to cloud storage and computing, enabling connection with robots, sensors, cameras, AR/VR, and other equipment.
During the lifetime of the Better Factory initiative, RAMP will provide a 3D simulation tool to create Digital Twin for virtual testing, a co-creation space for teams to collaborate online, among other digital services.
In addition, RAMP is a one-stop-shop for Manufacturing SMEs looking to find technologies and services such as:
(1) access to experts and infrastructure from regional Digital Innovation Hubs (DIHs)
(2) access to finance
(3) advanced training to reskill workers
(4) legal and business advice.
Introduction to APPS
APPS (Advanced Production Planning and Scheduling) is a combination of software services grouped per package, and hardware infrastructure for the optimization of waste, energy and resources, something that in the modern tech terminology is referred to as Lean-Agile Production, where technologies such as 3D-printing and in general Additive Manufacturing are introduced to create novel materials more efficiently (less energy), with a lower cost, better properties, and less waste.
APPS has been divided into 4 main packages:
(1) Logistics automation and optimization
(2) Production reconfiguration
(3) Cognitive HRI
(4) Resource optimization
Logistics and automation library
The Logistics automation and optimization module optimizes routes, agents, and material flows in production.
The objective of the Logistics library is to provide an easily deployable suite of applications for the rapid development of complete logistics solutions, including components for task scheduling, path planning, automatic factory layout generation and navigation.
Person Detection & Tracking
The Person Detection & Tracking system is intended to monitor the shared spaces between humans and robots, as it allows to detect people and track them using stereo pairs, obtaining the pose of each person detected in the navigation map.
The objective of the Agent Optimization package is to compute the optimal number of agents (AGVs, humans, etc.) for material transport.
Temporal Heatmap of Human Occupancy
The objective of the package is to create the temporal heatmaps that show for each square meter, and each one hour of each workday, the rate of human occupancy.
Real-Time Locating System
Production reconfiguration refers to the reconfiguration of the production line and the tasks of the automated and human actors (equipment, robots, workers) in the production floor, to produce different variants / personalization of a product.
Advanced Plant Modelling and 3D Digital Twin
The Advanced Plant Model (APM) aims to provide a real-time digital representation of the ongoing state of a given shop floor including the representation of workers, industrial and mobile robots, work-stations, manufacturing lines, racks, boxes, palettes, kits and parts, consolidated by a production schedule generated by a Manufacturing Execution Sytem (MES).
The Digital Twin Designer is the element inside the APM system that provides the means to enable the User to build the digital representation of manufacturing areas.
Manufacturing Process Management System
MPMS provides end-to-end manufacturing process management and orchestration of activities by: a) Modelling processes and agents, b) Executing in automated way the processes by assigning activities to agents (either human or automated), and c) Providing process monitoring for a complete status overview of the manufacturing process.
The cognitive HRI module supports Human Machine Collaboration (HMC) aiming at combining human flexibility with repeatability of automated factory entities, such as cobots, for improving working conditions while pursuing better performances.
Pose Recognition and Correction
Pose Recognition and Correction (PRaC) is a module that estimates the worker’s pose, performs ergonomic analysis and computes an ergonomic score based on camera images of the workers. By applying image processing algorithms to visual data this solution computes certain postures key figures, like the angles between arms and upper body, indicating the physical stress level of the observed working situation.
Fatigue Monitoring System
The Fatigue Monitoring System (FaMS) component detects possible psychological (e.g., loss of attention, mental fatigue) or physical (e.g., tiredness) discomfort or harmful situations for a worker. The situations identified by this component can be targeted by a short term intervention, which is an intervention that can be triggered and executed to support a specific worker during the current working shift.
The Intervention Manager (IM) component allows users to easily define intervention rules to orchestrate a production system. The component monitors the status of the worker-factory ecosystem in real-time, by elaborating data from sensors, machines, workers monitoring systems, ERP, and more. The set of intervention rules are known to the IM, which decides which is the best one to trigger.
Resource optimization package aims at optimizing the use of resources in terms of energy, resources, waste, through a data analytics tool that creates optimal solutions to minimize consumption. RAMP usage will guarantee real-time data visualization and time/effort resource optimization.
Business Process Optimization
The Business Process Optimization (BPO) module determines an optimized solution to the optimized motion task sequencing problem. BPO is focused on actions that have to be executed by factory floor agents, meaning any logistic entity (e.g., humans, AGVs, etc.), to carry out logistics motion tasks.
The objective of Process Optimisation is to perform process quality and efficiency optimisation using nonlinear model predictive control. The system learns the dynamics of the production process, and then it can predict the process output quality metrics given the current values for the control parameters.
Apache Superset app
Apache Superset is an open-source, enterprise-ready business intelligence web application allowing users to explore and visualize their data.
This section aims at providing non-technical learning units as additional support to the implementation of APPS technologies in your business, e.g., for building new business models.
The Business Training includes the training contents on KTE’s business-related tasks. An overview of the activities is provided, as well as a presentation of an exercise/tool to support the preparation of the business plan for each KTE.