Process Plan Controllers for Non-Deterministic Manufacturing Systems

Authors: Paolo Felli, Lavindra de Silva, Brian Logan, Svetan Ratchev

IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper we present an approach to the automated computation of process plans and process plan controllers. We extend previous work to support both nondeterministic (i.e., partially controllable) resources, and to allow operations to be performed in parallel on the same part. We show how implicit fairness assumptions can be captured in this setting, and how this impacts the definition of process plans. We extended previous approaches to the realisability and control problems for process recipes in manufacturing systems consisting of non-deterministic resources, and where operations can be performed in parallel on the same part. We formally defined the notions of process plans and process plan controllers for these systems...
Researcher Affiliation Academia 1Institute for Advanced Manufacturing, University of Nottingham, UK 2School of Computer Science, University of Nottingham, UK
Pseudocode Yes Algorithm 1 FINDSIM(R,P,s,r,s) and Algorithm 2 EVAL(R,P,Tcur,tr,τ,πb,σ0,Σ)
Open Source Code No The paper does not provide concrete access to source code for the methodology described within this specific paper. It references an accompanying video for a related work [de Silva et al., 2017] but no code repository for the paper's methodology.
Open Datasets No This is a theoretical paper that defines formal concepts and algorithms; it does not involve training models on datasets.
Dataset Splits No This is a theoretical paper that defines formal concepts and algorithms; it does not involve data splits for validation.
Hardware Specification No This is a theoretical paper that defines formal concepts and algorithms; it does not report on experiments that would require hardware specifications.
Software Dependencies No This is a theoretical paper that defines formal concepts and algorithms; it does not report on experiments that would require software dependencies with version numbers.
Experiment Setup No This is a theoretical paper that defines formal concepts and algorithms; it does not report on experiments that would require specific setup details like hyperparameters.