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Operations Research
Research Guide

What is Operations Research?

Operations Research applies mathematical optimization, linear programming, simulation, and stochastic modeling to solve decision problems in scheduling and resource allocation.

Operations Research (OR) encompasses techniques like linear programming and METRIC-type methods for spare parts stocking (Basten et al., 2012, 98 citations). Key texts cover practical approaches including action research variants (Arikunto, 2010, 579 citations; Arikunto, 1998, 93 citations). Recent works integrate OR with predictive maintenance and quality control (Lee et al., 2019, 141 citations).

Curated Papers

Key Challenges

Why It Matters

OR optimizes business operations such as inventory control, boosting performance in bottling companies (Ogbo and Ukpere, 2014, 80 citations). In manufacturing, OR supports lean Six Sigma for process capability in iron ore industries (Indrawati and Ridwansyah, 2015, 110 citations). Predictive maintenance ecosystems leverage OR for Industry 4.0 quality management (Lee et al., 2019, 141 citations), while integrated production-maintenance models reduce downtime (Bouslah et al., 2015, 123 citations; Iravani and Duenyas, 2002, 78 citations).

Key Research Challenges

Joint Repair and Stocking Optimization

Determining repair levels and spare parts stocking simultaneously challenges METRIC approximations in capital goods (Basten et al., 2012, 98 citations). Military contexts demand accurate failure predictions. Integrated models increase complexity (Goossens and Basten, 2015, 86 citations).

Deteriorating Systems Maintenance

Balancing production, quality control, and maintenance under deterioration with AOQL constraints requires joint optimization (Bouslah et al., 2015, 123 citations). Stochastic failures complicate scheduling. Predictive approaches emerge for Industry 4.0 (Lee et al., 2019, 141 citations).

Fuzzy Multi-Criteria Evaluation

Performance measurement in total productive maintenance uses fuzzy COPRAS amid imprecise data (Bekar et al., 2016, 117 citations). Comparative analysis across strategies is needed. Integration with TQM implementations varies (Permana et al., 2021, 80 citations).

Essential Papers

Prosedur Penelitian: Suatu Pendekatan Praktik (Edisi Revisi 2010)

Suharsini Arikunto · 2010 · 579 citations

Buku ini merupakan revisi dari buku Prosedur Penelitian Edisi Revisi VI. Pada revisi kali ini terdapat penambahan. Penambahan tersebut yaitu: Pertama: satu cara penelitian, yang semula hanya: op...

PROGRAM LINIER (TEORI DAN APLIKASI)

Yayu Nurhayati Rahayu, Opan Arifudin · 2020 · 225 citations

Setiap orang selalu dihadapkan pada suatu pengambilan keputusan. Model keputusan merupakan alat yang menggambarkan permasalahan keputusan sedemikian rupa sehingga memungkinkan identifikasi dan eval...

The quality management ecosystem for predictive maintenance in the Industry 4.0 era

Sang M. Lee, DonHee Lee, Youn Sung Kim · 2019 · International Journal of Quality Innovation · 141 citations

Abstract The Industry 4.0 era requires new quality management systems due to the ever increasing complexity of the global business environment and the advent of advanced digital technologies. This ...

Integrated production, sampling quality control and maintenance of deteriorating production systems with AOQL constraint

Bassem Bouslah, Ali Gharbi, Robert Pellerin · 2015 · Omega · 123 citations

FUZZY COPRAS METHOD FOR PERFORMANCE MEASUREMENT IN TOTAL PRODUCTIVE MAINTENANCE: A COMPARATIVE ANALYSIS

Ebru Turanoğlu Bekar, Mehmet Kemal Çakmakçı, Cengiz Kahraman · 2016 · Journal of Business Economics and Management · 117 citations

Modern manufacturing firms should be supported by effective maintenance to become successful in their operations. One of the approaches for improving the performance of maintenance activities is to...

Manufacturing Continuous Improvement Using Lean Six Sigma: An Iron Ores Industry Case Application

Sri Indrawati, Muhammad Ridwansyah · 2015 · Procedia Manufacturing · 110 citations

In Iron Ores Industry, manufacturing process capability is an important factor for business continuity. There are some problems faced in manufacturing process that caused inability to fulfill the m...

An approximate approach for the joint problem of level of repair analysis and spare parts stocking

Rob Basten, Matthijs C. van der Heijden, J.M.J. Schutten et al. · 2012 · Annals of Operations Research · 98 citations

Abstract For the spare parts stocking problem, generally METRIC type methods are used in the context of capital goods. A decision is assumed on which components to discard and which to repair upon ...

Reading Guide

Foundational Papers

Start with Arikunto (2010, 579 citations) for practical OR approaches including action research; then Basten et al. (2012, 98 citations) for METRIC spare parts models; Iravani and Duenyas (2002, 78 citations) for production-maintenance integration.

Recent Advances

Lee et al. (2019, 141 citations) for Industry 4.0 predictive quality; Bouslah et al. (2015, 123 citations) for deteriorating systems; Bekar et al. (2016, 117 citations) for fuzzy TPM evaluation.

Core Methods

Linear programming (Rahayu and Arifudin, 2020); METRIC approximations (Basten et al., 2012); fuzzy multi-criteria like COPRAS (Bekar et al., 2016); stochastic Markov processes (Iravani and Duenyas, 2002).

How PapersFlow Helps You Research Operations Research

Discover & Search

Research Agent uses searchPapers and citationGraph to map OR literature from Arikunto (2010, 579 citations), revealing clusters in linear programming and maintenance. exaSearch uncovers Indonesian texts like Rahayu and Arifudin (2020, 225 citations); findSimilarPapers extends to related stochastic models.

Analyze & Verify

Analysis Agent applies readPaperContent to extract METRIC methods from Basten et al. (2012), then runPythonAnalysis simulates inventory stocking with NumPy/pandas for statistical verification. verifyResponse (CoVe) and GRADE grading confirm claims on deteriorating systems (Bouslah et al., 2015).

Synthesize & Write

Synthesis Agent detects gaps in predictive maintenance OR via Lee et al. (2019), flags contradictions in fuzzy methods (Bekar et al., 2016). Writing Agent uses latexEditText, latexSyncCitations for OR models, latexCompile for reports, exportMermaid for optimization flowcharts.

Use Cases

"Simulate spare parts stocking from Basten et al. 2012 with Python."

Research Agent → searchPapers('Basten spare parts') → Analysis Agent → readPaperContent → runPythonAnalysis (NumPy METRIC simulation) → matplotlib plot of stocking levels.

"Write LaTeX review of linear programming in OR maintenance."

Research Agent → citationGraph('Rahayu linear programming') → Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (Arikunto 2010) → latexCompile PDF.

"Find GitHub code for fuzzy COPRAS in TPM."

Research Agent → searchPapers('Bekar fuzzy COPRAS') → Code Discovery → paperExtractUrls → paperFindGithubRepo → githubRepoInspect → verified implementation code.

Automated Workflows

Deep Research workflow conducts systematic review of 50+ OR papers on predictive maintenance, chaining searchPapers → citationGraph → structured report with GRADE scores. DeepScan applies 7-step analysis to linear programming models (Rahayu and Arifudin, 2020), including CoVe checkpoints and Python verification. Theorizer generates optimization theory from integrated maintenance literature (Bouslah et al., 2015).

Try Doxa for Operations Research Research

Frequently Asked Questions

What defines Operations Research?

Operations Research uses optimization algorithms, linear programming, simulation, and stochastic modeling for decisions in scheduling and resource allocation (Arikunto, 2010).

What are core OR methods?

Methods include METRIC for spare parts (Basten et al., 2012), linear programming (Rahayu and Arifudin, 2020), and fuzzy COPRAS for maintenance (Bekar et al., 2016).

What are key OR papers?

Foundational: Arikunto (2010, 579 citations), Basten et al. (2012, 98 citations). Recent: Lee et al. (2019, 141 citations), Bouslah et al. (2015, 123 citations).

What open problems exist in OR?

Challenges include joint repair-stocking optimization under uncertainty (Basten et al., 2012) and predictive maintenance in Industry 4.0 (Lee et al., 2019).