An Integer Batch Scheduling Model for a Single Machine with Simultaneous Learning and Deterioration Effects to Minimize Total Actual Flow Time

Yusriski, Rinto; Sukoyo,; Samadhi, T.M.A. Ari; Halim, Abdul Hakim

doi:10.1088/1757-899x/114/1/012073

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Note that TAF is based on the backward-scheduling approach. This objective was applied for various cases of BS problems (Surjandari et al, 2015;Yusriski et al, 2016;Maulidya et al, 2020), but the research pieces were for shop floors with JPMs. In reality, in many cases, the shop floor constitutes production lines with BPMs and multistage processes.…”

Section: Introductionmentioning

confidence: 99%

Single Item Batch-scheduling Model for a Flow Shop with m Batch-processing Machines to Minimize Total Actual Flow Time

Halim¹,

Hidayat²,

Aribowo³

2022

IJTech

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We propose a batch-scheduling model to minimize the total actual flow time (TAF) of parts to be processed in a flow shop consisting of m batch-processing machines. A batch-processing machine (BPM) is a machine that can process several parts at once, and the TAF of parts is the total interval time from the arrival times to the corresponding due date. In the real world, shop floors often have production lines with BPMs and multistage processes. We were motivated by a real problem in the aircraft industry and aimed to simultaneously satisfy the due dates and minimize the total time that parts spend in the shop. The problem was formulated as a mathematical model and solved using a proposed algorithm. The batch-scheduling problem is divided into batching and scheduling subproblems. The solution has been obtained by adopting backward scheduling. This paper develops a new model of flow shop scheduling problem for the shop with batch processing machines and the heuristic solution method. It provides numerical examples and their results to demonstrate the effectiveness of the proposed algorithm for solving the problem.

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Section: Introductionmentioning

confidence: 99%

Single Item Batch-scheduling Model for a Flow Shop with m Batch-processing Machines to Minimize Total Actual Flow Time

Halim¹,

Hidayat²,

Aribowo³

2022

IJTech

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show abstract

“…Model 3.6 (Yusriski et al 2016) The actual processing time function is Model 3.7 (Yusriski et al 2018) In manufacturing scenarios, it is highly unrealistic that the job processing time drops to zero precipitously with the increase of already processed jobs. Hence, a truncation parameter of ρ ∈ (0, 1) was introduced into p [ijr] = p ij r a , namely, p [ijr] = p ij max{r a , ρ} with a ≤ 0.…”

mentioning

confidence: 99%