TY - CHAP
T1 - Coping with Diverse Product Demand Through Agent-Led Type Transitions
AU - Obi, Martins
AU - Snider, Chris
AU - Giunta, Lorenzo
AU - Goudswaard, Mark
AU - Gopsill, James
PY - 2022/8/23
Y1 - 2022/8/23
N2 - Additive Manufacturing (AM) machines are a highly flexible manufacturing capability capable of producing a wide range of products. One feature that enables this is the ability to change materials in a relatively short time. For example, Fused Deposition Modelling (FDM) printers can be quickly and easily reconfigured to print in different materials such as PLA, ABS, and Nylon. Facilities that, therefore, employ Additive Manufacturing (AM) machines have the underlying capability to be flexible and responsive to diverse product demand. However, as jobs require different machine configurations for fabrication, methods need to be developed to assist facilities in deciding whether to and when to transition machines from one type of production to another to maximise overall system performance. In this paper, we explore how agent-based control can provide flexibility and responsiveness in manufacturing facilities. A model of a single fabrication workshop was created using AnyLogic, comprising multiple machines and incoming jobs of varying required machine configuration. The modelling shows responsiveness to spikes in demand when machines are able to request a change in configuration, although the penalties associated with reconfiguration cause poor performance when changes occur frequently. When not willing to change configuration, spikes in demand cause the system to become unstable and unable to meet changes in demand.
AB - Additive Manufacturing (AM) machines are a highly flexible manufacturing capability capable of producing a wide range of products. One feature that enables this is the ability to change materials in a relatively short time. For example, Fused Deposition Modelling (FDM) printers can be quickly and easily reconfigured to print in different materials such as PLA, ABS, and Nylon. Facilities that, therefore, employ Additive Manufacturing (AM) machines have the underlying capability to be flexible and responsive to diverse product demand. However, as jobs require different machine configurations for fabrication, methods need to be developed to assist facilities in deciding whether to and when to transition machines from one type of production to another to maximise overall system performance. In this paper, we explore how agent-based control can provide flexibility and responsiveness in manufacturing facilities. A model of a single fabrication workshop was created using AnyLogic, comprising multiple machines and incoming jobs of varying required machine configuration. The modelling shows responsiveness to spikes in demand when machines are able to request a change in configuration, although the penalties associated with reconfiguration cause poor performance when changes occur frequently. When not willing to change configuration, spikes in demand cause the system to become unstable and unable to meet changes in demand.
UR - https://link.springer.com/chapter/10.1007/978-981-19-3359-2_24
U2 - 10.1007/978-981-19-3359-2_24
DO - 10.1007/978-981-19-3359-2_24
M3 - Chapter
SN - 9789811933585 (hbk)
T3 - Smart Innovation, Systems and Technologies (SIST)
SP - 277
EP - 286
BT - Agents and Multi-Agent Systems: Technologies and Applications 2022
PB - Springer
ER -