The number of new disruptive technologies with expected global impact is growing on many fronts. Technologies such\u00a0as Advanced Robotics, big data analysis, the Internet of things or 3D printing are listed as drivers that will change “life, business and global economy”[MaChBuDoBiMa2013]. Looking into the past and from a manufacturing point of view,\u00a0the advent of such disruptive technologies, such as CAD\/CAM or internet, only fulfils its potential when the overall management practices adjust to the new reality.\u00a0Therefore, there is the need for an integrated development of these advanced manufacturing technologies with the\u00a0development of new multi-level decision-making tools. This is the main focus of this project.\u00a0Recent developments on Robotics are expected to change the landscape of the manufacturing processes. Robots\u00a0are nowadays interacting closely with humans, are<\/p>\n
Recent developments on Robotics are expected to change the landscape of the manufacturing processes. Robots\u00a0are nowadays interacting closely with humans, are programmable-by demonstration, easily pluggable in any point\u00a0of the shop-floor and capable of interacting in spaces designed for human use. This paradigm change has strong\u00a0implications on the development of future manufacturing decision-making tools.<\/p>\n
The main objective of the DM4Manufacturing project is the integrated development of manufacturing decision-making\u00a0tools aligned with the efficient use of advanced manufacturing technologies to address upcoming challenges in the\u00a0high-mix high customization industry. To fulfil the potential of Advanced Robotics in these scenario there is the need \u00a0for agile real-time decisions integrated in Adaptive Production Systems.\u00a0The project will pursue the following multidisciplinary challenges:Challenge 1 Optimal automation levels<\/p>\n
Challenge 1 Optimal automation levels
\nPlant managers and engineers in general struggle to adjust the level of automation of production lines to product\u00a0variations and market demand: especially when robots are involved, updates are slow, complex and cost-intensive,\u00a0and the loss of productivity is considerable due to a stopped manufacturing line. The most common solution is to\u00a0keep the level of automation deliberately low to guarantee the fast updatability of the system. Another solution is to\u00a0simply design the manufacturing lines from the start for the maximum estimated customer demand, but this means\u00a0high initial investment and low equipment utilization during large parts of the product cycle and a huge difficulty to\u00a0change the product.<\/p>\n
Challenge 2 – Human-centered automation
\nThe flexibility of the robotic systems to perform a variety of tasks is increasing but the major benefit from the use\u00a0of collaborative robotics comes from the close cooperation with humans, exploring the best abilities of humans and\u00a0robots. To maximize this potential, there is the need for decision making tools that can cope the robot\/machine\u00a0limitations with the human dimension in ergonomic, social and productivity terms.<\/p>\n
Challenge 3 – Simulation and Optimization tools for adaptive production systems
\nScheduling and controlling manufacturing activities in a dynamic environment, subject to a high level of uncertainty\u00a0imposed by various unexpected events like machine breakdowns or frequent changes in orders quantity, mix and due\u00a0dates, is a difficult task. Additionally, increased flexibility allowed by new manufacturing technologies, like robotics,\u00a0has amplified, rather than reduced, planning, scheduling and control problems. Thus, novel optimization, simulation\u00a0or simulation based optimization tools are required to, not only generate robust production schedules, but also to\u00a0undertake real-time rescheduling to cope with the production environment uncertainty.<\/p>\n","protected":false},"excerpt":{"rendered":"
Motivation The number of new disruptive technologies with expected global impact is growing on many fronts. Technologies such\u00a0as Advanced Robotics, big data analysis, the Internet of things or 3D printing are listed as drivers that will change “life, business and global economy”[MaChBuDoBiMa2013]. Looking into the past and from a manufacturing point of view,\u00a0the advent of […]<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-19","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/pages\/19","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/comments?post=19"}],"version-history":[{"count":3,"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/pages\/19\/revisions"}],"predecessor-version":[{"id":51,"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/pages\/19\/revisions\/51"}],"wp:attachment":[{"href":"https:\/\/dm4manufacturing.inesctec.pt\/index.php\/wp-json\/wp\/v2\/media?parent=19"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}