Hybrid ASP-based multi-objective scheduling of semiconductor manufacturing processes (Extended version)

TL;DR

This paper presents a hybrid ASP-based approach for multi-objective scheduling in semiconductor manufacturing, addressing complex, realistic production processes with diverse machines and operations, aiming for large-scale optimization.

Contribution

It introduces a novel hybrid Answer Set Programming model tailored for semiconductor manufacturing, handling complex constraints and multiple objectives beyond traditional heuristic methods.

Findings

Effective modeling of complex manufacturing constraints

Improved scheduling solutions for large-scale processes

Potential for multi-objective optimization in industry

Abstract

Modern semiconductor manufacturing involves intricate production processes consisting of hundreds of operations, which can take several months from lot release to completion. The high-tech machines used in these processes are diverse, operate on individual wafers, lots, or batches in multiple stages, and necessitate product-specific setups and specialized maintenance procedures. This situation is different from traditional job-shop scheduling scenarios, which have less complex production processes and machines, and mainly focus on solving highly combinatorial but abstract scheduling problems. In this work, we address the scheduling of realistic semiconductor manufacturing processes by modeling their specific requirements using hybrid Answer Set Programming with difference logic, incorporating flexible machine processing, setup, batching and maintenance operations. Unlike existing methods that schedule semiconductor manufacturing processes locally with greedy heuristics or by independently optimizing specific machine group allocations, we examine the potentials of large-scale scheduling subject to multiple optimization objectives.