Effect of Routing Flexibility on the Performance of Order Release Policies in a Flexible Job Shop with Sequence-Dependent Setup Time: A Simulation Study

Rani, Sushma; Jain, Anuj; Angra, Surjit

doi:10.1080/23080477.2022.2040205

Cited by 3 publications

(11 citation statements)

References 40 publications

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“…They concluded that the proposed methodology improves system performance when combined with a consistent forecasting system. Rani et al 23) investigated the routing flexibility effect in a job shop while considering order release and SDST. The system's performance was evaluated in terms of MTT, MLT, TS, and mean tardiness performance measures.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the present study, the arrival of jobs is considered stochastic and dynamic. The number of operations on a job varies between 4 to 6 with uniform distribution 4,12,23) . The processing time of jobs on different machines varies from U(6,7) to U (18,19).…”

Section: Job Datamentioning

confidence: 99%

“…The processing time of jobs on different machines varies from U(6,7) to U (18,19). PRD sequencing rule is used to arrange the jobs in PSP 4,12,23) . To choose jobs from the machine queue, a dispatching rule is applied, i.e., similar setup plus shortest processing time 7) .…”

Section: Job Datamentioning

confidence: 99%

“…It is the average time between two job arrivals (λ). It is determined by the formula given below 8,23,25) .…”

Section: Mean Inter-arrival Timementioning

confidence: 99%

“…The value of µg is 4.83 for the given input data. This study considers six machines 4,12,23,26) with 80%, 85%, and 90% shop utilization. In addition, the predicted shop load is within a range of ±1.5% of the considered shop utilization level due to stochastic processing and setup time 8) .…”

Section: Mean Inter-arrival Timementioning

confidence: 99%

See 4 more Smart Citations

Assessing the Effect of Setup Times and Shop Utilization Levels on Performance of ORR Policies in a Stochastic Dynamic Job Shop with Sequence-Dependent Setup Times: A Simulation Approach

Rani¹,

Jain²,

Angra³

2022

Evergreen

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Order review and release (ORR) controls making jobs from planning stage to execution stage. This article assesses the effect of setup times and shop utilization levels on ORR policies performance in stochastic dynamic job shop (SDJS) considering sequence-dependent setup time (SDST). The system performance indicators such as mean throughput time (MTT), mean lead time (MLT), number of tardy jobs (NOTJ), and total setups (TS) are used to assess system's performance. For conducting experiments, the simulation model is created using Promodel ® simulation software. Results indicate that for a given ORR policy, at a given setup time and shop utilization level, as workload trigger level, increases MTT increases. In contrast, the other performance measures such as MLT, NOTJ, and TS decrease. Further, for a given ORR policy, as shop utilization decreases, MTT, MLT, and NOTJ decrease at all workload trigger levels for all setup time levels. In contrast, TS increase at all workload trigger levels for all setup time levels. Further, as setup time increases for a given ORR policy, MTT and MLT increase at all workload trigger levels for all shop utilization levels. In contrast, TS and NOTJ decrease.

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Section: Literature Reviewmentioning

confidence: 99%