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Cited by 1Scheduling and Optimization AlgorithmsManagement and Optimization TechniquesAdvanced Manufacturing and Logistics Optimization

Assessment of Production Costs in Toyota Production System Simulation Based on Makespan

Open access
MANGNGENRE, Saiful, INDAH, A. Besse Riyani, IKASARY, Diniary, HAMZI, Ahmed, NOVAWANDA, Olyvia·2025·Management and Production Engineering Review
DOI 10.24425/mper.2025.156146
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Abstract

This study examines the impact of makespan on production costs by comparing the Toyota Production System through simulations with three scheduling algorithms.

AI snapshot

Written from the paper’s full text.

TL;DR

This simulation study compares Initial, Simulated Annealing, and Tabu Search scheduling in a Toyota Production System setting across three demand levels, tracking makespan, total production cost, and unit cost. It reports a time–cost trade-off, with metaheuristics showing better unit-cost economies at higher demand but higher total costs, while the makespan direction is internally inconsistent between the narrative and tables.

Key findings

  • For demands of 186, 216, and 246 units, Simulated Annealing and Tabu Search produced identical results. Their total production costs were higher than the Initial Method: $245,229 vs $237,377; $283,881 vs $276,350; and $322,534 vs $315,323, an increase of roughly 2.3–3.3%.
  • Unit costs moved in opposite directions: the Initial Method rose from $1,276 to $1,282, while Simulated Annealing/Tabu Search fell from $1,318 to $1,311, which the paper interprets as better economies of scale at higher volumes.
  • The narrative reports that Simulated Annealing and Tabu Search reduced makespan by about 2.2–3.2% (e.g., 569.67 vs 588.54 minutes at Demand 1), but Table 2 lists the Initial Method at 569.68, 663.29, and 756.90 minutes and Simulated Annealing/Tabu Search at 588.54, 681.38, and 774.22 minutes, reversing that direction.
  • Simulated Annealing used different job sequences across demands yet matched Tabu Search in cost and makespan, suggesting job order may not materially affect outcomes when the optimization method is effective.

Methods

  • Quantitative simulation experiment comparing three scheduling approaches—Initial Method, Simulated Annealing, and Tabu Search—for a vehicle production system with six vehicle types and four workstations.
  • Three demand scenarios were used: 186, 216, and 246 units. Production cost was calculated as TC = (CL + CM + CE + CO) × M, with fixed, labor, and per-workstation production costs; Microsoft Excel was used for simulation and analysis.
  • The study compared makespan, total production cost, and unit cost, examined time–cost relationships, and validated the model against historical data or industry benchmarks and internal consistency checks.

Limitations

  • The paper states that the demand range was restricted and external factors were excluded; the cost model also omitted production quality, downtime, and failure rate.
  • The paper notes that the identical Simulated Annealing and Tabu Search results need further investigation, possibly due to a narrow solution space or parameter settings, and that linearity may not hold at much wider production volumes.
  • Evident from the text: the makespan results are contradictory—the narrative and abstract/conclusion describe metaheuristics as achieving shorter makespan, while Table 2 shows the Initial Method with lower makespan values—which limits confidence in the reported makespan–cost relationship.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.24425/mper.2025.156146

Cites

0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 4 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Simulated Annealing and Tabu Search unit cost decreased from $1,318 at Demand 1 to $1,311 at Demand 3.

    “The Unit Cost Analysis provides additional insight that Initial Method: Unit Cost increased slightly from $1,276 (Request 1) to $1,282 (Request 3) and Simulated Annealing/Tabu Search: Unit Cost decreased from $1,318 (Request 1) to $1,311 (Request 3).”
    Quote in the paperSubstantial claim
  • Findingown data

    Initial Method unit cost increased slightly from $1,276 at Demand 1 to $1,282 at Demand 3.

    “The Unit Cost Analysis provides additional insight that Initial Method: Unit Cost increased slightly from $1,276 (Request 1) to $1,282 (Request 3) and Simulated Annealing/Tabu Search: Unit Cost decreased from $1,318 (Request 1) to $1,311 (Request 3).”
    Quote in the paperNot a substantial claim
  • Findingown data

    A makespan reduction of approximately 3.2% by Simulated Annealing and Tabu Search results in a cost increase of between 2.3% and 3.3%.

    “Based on the Efficiency Trade-off, a makespan reduction of approximately 3.2% by Simulated Annealing and Tabu Search results in a cost increase of between 2.3% to 3.3%.”
    Quote in the paperSubstantial claim
  • Interpretationown data

    Job order may not significantly affect costs or makespan as long as the optimization method used is effective.

    “This indicates that in this case, job order may not significantly affect costs or makespan as long as the optimization method used is effective.”
    Quote in the paperSubstantial claim
  • Interpretationown data

    Simulated Annealing and Tabu Search have the potential to achieve better economies of scale at higher production volumes, indicated by a decrease in unit cost as demand increases.

    “This trend shows that although Simulated Annealing and Tabu Search result in higher Total Production Costs, these methods have the potential to achieve better economies of scale at higher production volumes.”
    • Also stated in: § Conclusions · hedged
      “Unit Cost analysis reveals that Simulated Annealing and Tabu Search have the potential to achieve better economies of scale at high production volumes, indicated by a decrease in Unit Cost as demand increases.”
    Quote in the paperSubstantial claim
  • May combine two claims. 7
  • Classified as probably not a substantial claim. 2

  • May combine two claims.

    Findingown data

    There is an inverse relationship between makespan and production costs: the Initial Method with the longest makespan produces the lowest costs, while Simulated Annealing and Tabu Search with shorter makespans produce higher costs.

    “The data shows that there is an inverse relationship between makespan and production costs.The Initial Method with the longest makespan produces the lowest costs, while Simulated Annealing and Tabu Search with shorter makespans produce higher costs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The increase in makespan and costs from Demand 1 to Demand 2 and Demand 3 is relatively consistent for all methods, showing a relationship that tends to be linear between makespan, costs, and production volume in the analyzed demand range.

    “The increase in makespan and costs from Demand 1 to Demand 2 and Demand 3 is relatively consistent for all methods.This shows a relationship that tends to be linear between makespan, costs, and production volume in the analyzed demand range.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Simulated Annealing and Tabu Search produce identical makespan and shorter makespan than the Initial Method for all demand levels, with reductions of 3.2%, 2.7%, and 2.2% for Demand 1, 2, and 3 respectively.

    “Results show that SA and TS achieve a lower makespan than the Initial Method, although their total production costs are slightly higher.”
    • Also stated in: § Makespan · plain
      “Based on the image above, the data shows that Simulated Annealing and Tabu Search produce identical and shorter makespan compared to the Initial Method for all levels of demand showing results Demand 1: 569.67 minutes vs 588.54 minutes (3.2% reduction), Demand 2: 663.27 minutes vs 681.38 minutes (2.7% reduction), and Demand 3: 756.91 minutes vs 774.22 minutes (2.2% reduction).”
    • Also stated in: § Conclusions · plain
      “The results show that Simulated Annealing and Tabu Search produce shorter makespan compared to the Initial Method, with a reduction of around 2.2-3.2% for various demand levels.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Despite producing shorter makespan, Simulated Annealing and Tabu Search produce higher Total Production Cost than the Initial Method, with increases of 3.3%, 2.7%, and 2.3% for Demand 1, 2, and 3 respectively.

    “Interestingly, despite producing shorter makespan, Simulated Annealing and Tabu Search actually produce higher Total Production Cost as shown in Table 3 from Demand 1: $245,229 vs $237,377 (3.3% increase), Demand 2: $283,881 vs $276,350 (2.7% increase), and Demand 3: $322,534 vs $315,323 (2.3% increase).”
    • Also stated in: § Conclusions · plain
      “Interestingly, even though it produces a shorter makespan, Simulated Annealing and Tabu Search actually produce a higher Total Production Cost, with an increase of 2.3-3.3%.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    All methods have good scalability in dealing with increasing demand.

    “Meanwhile, Production Flexibility shows that all methods have good scalability in dealing with increasing demand.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    The study's demand range is restricted and external factors were excluded.

    “Limitations include a restricted demand range and the exclusion of external factors, suggesting areas for further research on production quality in manufacturing.”
    • Also stated in: § Makespan and Cost Relationship · plain
      “In this study, factors such as production quality, downtime, and failure rate were not included in the cost model.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Production processes that require shorter time usually show higher efficiency and allow for reduced production costs.

    “Production processes that require shorter time usually show higher efficiency and allow for reduced production costs (Pinedo 2022).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Pinedo 2022 source

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Model validation was carried out by comparing simulation results with historical data or industry benchmarks, as well as checking internal consistency of the model.

    “Model validation is carried out by comparing simulation results with historical data or industry benchmarks, as well as checking the internal consistency of the model to ensure the reliability of the results.”
    Quote in the paperSubstantial claim
8 of 8

  • The paper relies on this without support.

    The per-unit-time cost components (labor, machine, energy, and other costs) are constant across the three scheduling methods and demand levels.

    “Calculation of production costs uses the formula TC = (CL + CM + CE + CO) × M where TC is Total Cost, CL is Labor Cost, CM is Machine Cost, CE is Energy Cost, CO is Other Costs, and M is Makespan (Pinedo 2022).”
1 of 1

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Makespan ranking is reversed in the conclusions

    Major

    Table 2 gives the Initial Method a shorter makespan than Simulated Annealing and Tabu Search at every demand level. The discussion says the Initial Method has the longest makespan, so its claimed time-cost trade-off rests on the opposite ranking from the reported results.

1 of 1

Cites

The publisher hasn’t deposited this paper’s reference list.

Research works printed but not linked: 9

  1. [4]4. Chase, R., & Jacobs, F. (2021). Operations and Supply Chain Management (16th ed.). New York: McGraw- Hill Education.
  2. [5]5. Drury, C. (2018). Management and Cost Accounting (10th ed.). Andover: Cengage Learning.
  3. [6]6. Heizer, J., Render, B., & Munson, C. (2023). Opera- tions Management: Sustainability and Supply Chain Mangement (14th ed.). Edinburgh: Pearson Education Limited.
  4. [7]7. Horngren, C., Datar, S., & Rajan, M. (2012). Cost Ac- counting A Managerial Emphasis (14th ed.). Harlow: Pearson Education.
  5. [13]13. Liker, J. (2004). The Toyota Way: 14 Management Prin- ciples from The World's Greatest Manufacturer. New York: McGraw-Hill.
  6. [15]15. Monden, Y. (2011). TOYOTA Production System an Integrated Approach to Just-in-Time (4th ed.). New York: CRC Press.
  7. [22]22. Pindyck, R., & Rubinfeld, D. (2020). Microeconomics (9th ed.). Barkeley: Pearson.
  8. [25]25. Rother, M., Shook, J., Womack, J., & Jones. (2003). Learning to See: Value Stream Mapping to Add Value and Eliminate (1st ed.). Boston: Learn Enterprise Institute.
  9. [30]30. Slack, N., Brandon-Jones, A., & Johnston, R. (2013). Operation Management (7th ed.). Upper Saddle River: Pearson Education.

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Authors
MANGNGENRE, S., INDAH, A. B. R., IKASARY, D., HAMZI, A., & NOVAWANDA, O.
Affiliations
  • Hasanuddin University (ID)
  • Jazan University (SA)
  • University of Surabaya (ID)
Venue
Management and Production Engineering Review
Publisher
Polish Academy of Sciences Chancellery
Published
2025-09-30
ISSN
  • 2080-8208 (ISSN-L)
  • 2082-1344
DOI
10.24425/mper.2025.156146
OpenAlex
W7106302438
Cited by
0
References
0
FWCI
0.00
Type
journal article
Language
pl
Open access
Locations
Management and Production Engineering Review (publishedVersion)
Funders
Universitas Hasanuddin
Topics
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Scheduling and Optimization Algorithms
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Management and Optimization Techniques
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Advanced Manufacturing and Logistics Optimization
Keywords
Toyota Production System, makespan, production costs, scheduling algorithms, simulated annealing, tabu search, demand level, unit cost, economies of scale, time-cost trade-off, break-even point, production constraints, technology investment

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