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Multi-product scheduling through process mining: bridging optimization and machine process intelligence

https://doi.org/10.1007/s10845-021-01767-2
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4612-4380-9_41openalex-snapshot
Bootstrap Methods: Another Look at the Jackknife
inferredcites →https://doi.org/10.1007/978-1-4614-2361-4openalex-snapshot
Scheduling
inferredcites →https://doi.org/10.1007/978-3-319-52250-0openalex-snapshot
Design and Analysis of Experiments
inferredcites →https://doi.org/10.1007/978-3-662-49851-4openalex-snapshot
Process Mining: Data Science in Action
inferredcites →https://doi.org/10.1007/978-3-662-49851-4_1openalex-snapshot
Data Science in Action
inferredcites →https://doi.org/10.1007/s00170-006-0561-zopenalex-snapshot
Development of a genetic algorithm for scheduling products with a multi-level structure
inferredcites →https://doi.org/10.1007/s00170-008-1653-8openalex-snapshot
Development of a multiobjective GA for advanced planning and scheduling problem
inferredcites →https://doi.org/10.1007/s00521-014-1678-xopenalex-snapshot
Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem
inferredcites →https://doi.org/10.1007/s10845-008-0207-0openalex-snapshot
Rolling-horizon and fix-and-relax heuristics for the multi-product multi-level capacitated lotsizing problem with sequence-dependent setups
inferredcites →https://doi.org/10.1007/s10845-018-1434-7openalex-snapshot
Establishment of maintenance inspection intervals: an application of process mining techniques in manufacturing
inferredcites →https://doi.org/10.1007/s11518-011-5180-zopenalex-snapshot
A case study for advanced planning and scheduling (APS)
inferredcites →https://doi.org/10.1016/0305-0548(95)00079-8openalex-snapshot
Simulated annealing and genetic algorithms for scheduling products with multi-level product structure
inferredcites →https://doi.org/10.1016/0360-8352(96)00047-2openalex-snapshot
A tutorial survey of job-shop scheduling problems using genetic algorithms—I. representation
inferredcites →https://doi.org/10.1016/0378-4754(82)90066-0openalex-snapshot
Petri Net theory and the modeling of systems
inferredcites →https://doi.org/10.1016/j.aei.2016.11.007openalex-snapshot
A review of essential standards and patent landscapes for the Internet of Things: A key enabler for Industry 4.0
inferredcites →https://doi.org/10.1016/j.apm.2013.05.049openalex-snapshot
Operational extended model formulations for Advanced Planning and Scheduling systems
inferredcites →https://doi.org/10.1016/j.asoc.2014.08.024openalex-snapshot
A survey on the Imperialist Competitive Algorithm metaheuristic: Implementation in engineering domain and directions for future research
inferredcites →https://doi.org/10.1016/j.cirp.2016.04.022openalex-snapshot
An approach for process control of responsive service processes
inferredcites →https://doi.org/10.1016/j.cose.2018.06.002openalex-snapshot
Anomaly detection for industrial control systems using process mining
inferredcites →https://doi.org/10.1016/j.ejor.2006.06.018openalex-snapshot
A mixed integer programming model for advanced planning and scheduling (APS)
inferredcites →https://doi.org/10.1016/j.ejor.2010.09.022openalex-snapshot
Multi-level single machine lot-sizing and scheduling with zero lead times
inferredcites →https://doi.org/10.1016/j.ejor.2013.06.021openalex-snapshot
Multi-level lot sizing and job shop scheduling with compressible process times: A cutting plane approach
inferredcites →https://doi.org/10.1016/j.eswa.2019.05.003openalex-snapshot
Process mining techniques and applications – A systematic mapping study
inferredcites →https://doi.org/10.1016/j.eswa.2020.113545openalex-snapshot
Robust scheduling based on extreme learning machine for bi-objective flexible job-shop problems with machine breakdowns
inferredcites →https://doi.org/10.1016/j.ifacol.2019.11.378openalex-snapshot
Prediction of variable technological operation times in production jobs scheduling
inferredcites →https://doi.org/10.1016/j.is.2015.07.003openalex-snapshot
A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs
inferredcites →https://doi.org/10.1016/j.jclepro.2016.06.161openalex-snapshot
A multi-level optimization approach for energy-efficient flexible flow shop scheduling
inferredcites →https://doi.org/10.1016/j.jmsy.2020.06.003openalex-snapshot
An extended model for remaining time prediction in manufacturing systems using process mining
inferredcites →https://doi.org/10.1016/j.procir.2014.02.001openalex-snapshot
Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment
inferredcites →https://doi.org/10.1016/j.procir.2016.07.040openalex-snapshot
A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises
inferredcites →https://doi.org/10.1016/s0925-5273(02)00104-4openalex-snapshot
Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products
inferredcites →https://doi.org/10.1023/a:1012292102123openalex-snapshot
A two phase optimization method for Petri net models of manufacturing systems
inferredcites →https://doi.org/10.1023/a:1019920324813openalex-snapshot
Robust design of flexible manufacturing systems using, colored Petri net and genetic algorithm
inferredcites →https://doi.org/10.1080/00207543.2013.848487openalex-snapshot
Multi-level job scheduling in a flexible job shop environment
inferredcites →https://doi.org/10.1080/00207543.2017.1372647openalex-snapshot
The industrial management of SMEs in the era of Industry 4.0
inferredcites →https://doi.org/10.1080/00207543.2017.1413259openalex-snapshot
A comprehensive survey of ubiquitous manufacturing research
inferredcites →https://doi.org/10.1080/00207543.2018.1459923openalex-snapshot
A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry
inferredcites →https://doi.org/10.1080/15458830.1996.11770714openalex-snapshot
Scheduling: Theory, Algorithms, and Systems
inferredcites →https://doi.org/10.1093/biomet/52.3-4.591openalex-snapshot
An Analysis of Variance Test for Normality (Complete Samples)
inferredcites →https://doi.org/10.1093/comjnl/25.1.129openalex-snapshot
Petri Net Theory and the Modeling of Systems
inferredcites →https://doi.org/10.1108/01443570210417623openalex-snapshot
Critical factors of MRP implementation in small and medium‐sized firms
inferredcites →https://doi.org/10.1108/bpmj-02-2018-0051openalex-snapshot
Discovering high-level BPMN process models from event data
inferredcites →https://doi.org/10.1108/bpmj-06-2017-0148openalex-snapshot
How is process mining technology used by organizations? A systematic literature review of empirical studies
inferredcites →https://doi.org/10.1108/s1475-1488(2010)0000013005openalex-snapshot
Technology monoculture: ERP systems, “techno-process diversity” and the threat to the information technology ecosystem
inferredcites →https://doi.org/10.1109/5.24143openalex-snapshot
Petri nets: Properties, analysis and applications
inferredcites →https://doi.org/10.1109/access.2019.2923624openalex-snapshot
A Method for Mining Process Models With Indirect Dependencies via Petri Nets
inferredcites →https://doi.org/10.1109/tkde.2004.47openalex-snapshot
Workflow mining: discovering process models from event logs
inferredcites →https://doi.org/10.1214/aos/1176344552openalex-snapshot
Bootstrap Methods: Another Look at the Jackknife
inferredcites →https://doi.org/10.1287/ijoc.6.2.154openalex-snapshot
Genetic Algorithms and Random Keys for Sequencing and Optimization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4118114openalex-extracted
Interactive Process Drift Detection for Condition-Based Maintenance Using Process Mining Techniques
inferred← citeshttps://doi.org/10.2139/ssrn.4690886openalex-extracted
Process Mining in Manufacturing and Logistics: A Systematic Mapping and New Taxonomy Proposal
inferred← citeshttps://doi.org/10.1007/978-3-031-82225-4_3openalex-snapshot
EVErPREP: Towards an Event Knowledge Graph Enhanced Workflow Model for Event Log Preparation
inferred← citeshttps://doi.org/10.1007/978-981-19-5272-2_2openalex-snapshot
Process Mining in Healthcare: Challenges and Promising Directions
inferred← citeshttps://doi.org/10.1007/978-981-96-5257-0_4openalex-snapshot
Optimization Methods in Production Planning and Scheduling
inferred← citeshttps://doi.org/10.1007/s10845-026-02792-9openalex-snapshot
A process mining and machine learning based approach for remaining time prediction of production orders
inferred← citeshttps://doi.org/10.1016/j.aei.2025.103397openalex-snapshot
Interactive Process Drift Detection (IPDD) for condition-based maintenance using process mining
inferred← citeshttps://doi.org/10.1016/j.jmsy.2021.08.005openalex-snapshot
Discovery of path-attribute dependency in manufacturing environments: A process mining approach
inferred← citeshttps://doi.org/10.1016/j.procir.2025.01.004openalex-snapshot
Uncovering the potential and pitfalls of Process Mining in manufacturing
inferred← citeshttps://doi.org/10.1016/j.procs.2024.06.428openalex-snapshot
Scheduling Molds Manufacturing Processes through Process Mining
inferred← citeshttps://doi.org/10.1108/gs-09-2024-0110openalex-snapshot
Identifying the maturity level of ERP systems implementation and use in SMEs: a study using grey fixed weight clustering
inferred← citeshttps://doi.org/10.1108/ijlss-04-2022-0092openalex-snapshot
Agile DMAIC cycle: incorporating process mining and support decision
inferred← citeshttps://doi.org/10.24874/pes.si.01.010openalex-snapshot
OPTIMIZING PRODUCTION SCHEDULING THROUGH HYBRID DYNAMIC GENETIC-ADAPTIVE IMPROVED GRAVITATIONAL OPTIMIZATION ALGORITHM
inferred← citeshttps://doi.org/10.3390/su16041694openalex-snapshot
Eliminating Non-Value-Added Activities and Optimizing Manufacturing Processes Using Process Mining: A Stock of Challenges for Family SMEs
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