Tag Archives: 3D Printing Production Planning

3D Printing Where and How: 3DP-RDM network event – 31st January

What: Final dissemination event of the 3DP-RDM network
Where: IfM, Cambridge
When: 31st January 2017
How: Register your participation on Eventbrite

Following the completion of the second round of 3DP-RDM feasibility studies you are warmly invited to join this dissemination event to hear the final results of these studies. This EPSRC-funded event will feature presentations from the four 3DP-RDM feasibility studies conducted during 2016. Registration for this event is free but tickets are limited. Register your participation on Eventbrite.

Provisional Agenda

12:30  Lunch, registration and networking
13:30  Welcome and introductions
13:45  Overview of 3DP-RDM
14:00  Supporting SMEs in creating value through 3DP-RPM, Dr Peter Dorrington, Cardiff Metropolitan University
14:45  3D Printing Production Planning (3DPPP): reactive manufacturing execution driving re-distributed manufacturing, Dr Martin Baumers, University of Nottingham
15:30  Refreshments and networking
16:00  A feasibility study of mass customisation governance: regulation, liability, and intellectual property of re‐distributed manufacturing in 3D printing, Dr Phoebe Li, University of Sussex
16:45  Driving Innovation in Redistributed Manufacturing: A Comparative Study in the British and Italian Motorsport Valleys, Dr Paolo Aversa, City University, and Dr Sebastiano Massaro, University of Warwick
17:30  Summary
17:45  Close and networking

[Image source]


Introducing the 3DP-RDM Feasibility Studies: 3D Printing Production Planning

Following the recent feasibility study competition, the 3DP-RDM network is funding four projects in 2016. In this series of blog posts we introduce the four studies. Today we introduce the final study, “3D Printing Production Planning (3DPPP): reactive manufacturing execution driving re-distributed manufacturing”, which is being led by Dr Martin Baumers at the University of Nottingham.

As an emerging manufacturing technology, Additive Manufacturing (AM) is demonstrating significant opportunities across a wide range of industrial sectors. Among the advantages of the technology are an ability to generate complex functional geometries and the technology’s efficiency in the manufacture of small numbers of products.

In most industries, however, AM faces the challenge of substituting, or integrating with, conventional manufacturing technologies, which are normally operated in a centralised location. Among the reasons for the dominance of centralised manufacturing are economies of scale, allowing the amortization of substantial costs over large volumes of products for the global marketplace. Additionally, the ability to implement suitable supply chain configurations has evolved from being an afterthought to a core capability for manufacturing businesses.

Viewing the work flow of AM in this context reveals a puzzle: the current process for allocating build requirements to individual (potentially re-distributed) AM systems, and thereby configuring the AM supply chain, relies on isolated and disconnected decisions on the operator/technician level. This is not indicative of efficient manufacturing order execution and effective supply chains.

As a collaboration between the 3D Printing Research Group (3DPRG) and the Automated Scheduling and Planning Research Group (ASAP), both at the University of Nottingham, this project is exploring the feasibility of adopting an optimisation-based manufacturing execution methodology that complements the strengths of AM. Essentially, the idea is to replace the existing process by a combined automated “all-in-one” production planning tool driven by a set of interchangeable build volume packing and scheduling heuristics. Considering a wide range of general and location-related aspects, the tool allows the determination of the best AM system for a build request, including the benefits resulting from re-distribution.

The tool under development is called the 3D Packing Research Application Tool (yes, the acronym is “3DPackRAT”…). In essence, it is a custom developed manufacturing execution platform to explore and deploy various algorithms, heuristics and policies to optimise the work flow in AM, both for the centralised and re-distributed settings. This should allow the release of significant additional value by making the process more effective, potentially enabling adopters to leapfrog the gradual evolution of supply chain management in response to AM as a new technology. More information, including a video walk through of the demonstrator, is available on the project website.

Project Group at the University of Nottingham: Martin Baumers, Ender Ozcan, Jason Atkin, Warren Jackson, Wenwen Li

Industrial advisers: Susan Reiblein (HP Enterprise), David Knight (Knightgraphics)

[Image source: Martin Baumers]