How Many Parts to Make at Once¶
Harris, F. W. (1913). How Many Parts to Make at Once. Factory: The Magazine of Management, 10(2), 135-136.
Cited by¶
3 citations across 3 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Batch Processing
- Recognising the pattern enables the batch-size optimisation: the relationship between fixed setup cost, per-item processing cost, and arrival rate determines an optimal batch size at which marginal latency cost balances marginal setup-amortisation gain, and the same calculation appears in inventory theory, in deferred-compilation decisions, and in grading workflow.
This sourceOriginal economic-lot-size (EOQ) derivation balancing fixed setup cost against per-item holding cost to find an optimal batch.
- Recognising the pattern enables the batch-size optimisation: the relationship between fixed setup cost, per-item processing cost, and arrival rate determines an optimal batch size at which marginal latency cost balances marginal setup-amortisation gain, and the same calculation appears in inventory theory, in deferred-compilation decisions, and in grading workflow.
- Batch Size
- The canonical clean instantiation is the economic order quantity, whose substrate- independent form — optimum batch size scales as the square root of the ratio of setup cost to flow cost — is itself portable.
This sourceDerives the economic order quantity Q* = √(2SD/H), the closed-form interior optimum balancing fixed setup cost against per-item holding cost.
- The canonical clean instantiation is the economic order quantity, whose substrate- independent form — optimum batch size scales as the square root of the ratio of setup cost to flow cost — is itself portable.
Mechanisms¶
- Economic Order Quantity Model
- Because the curve is convex, that point is a unique closed-form optimum — the square-root EOQ formula.
This sourceDerives the unique cost-minimizing economic lot size as a square-root formula from setup and carrying costs.
- Because the curve is convex, that point is a unique closed-form optimum — the square-root EOQ formula.
Verification¶
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Links previously used in the corpus¶
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