scholarly journals A batch scheduling model for a three-stage flow shop with job and batch processors considering a sampling inspection to minimize expected total actual flow time

2021 ◽  
Vol 14 (3) ◽  
pp. 520
Author(s):  
Pratya Poeri Suryadhini ◽  
Sukoyo Sukoyo ◽  
Suprayogi Suprayogi ◽  
Abdul Hakim Halim
Keyword(s):  
Flow Shop ◽  
Flow Time ◽  
Batch Scheduling ◽  
Batch Processor ◽  
The Third ◽  
Sampling Inspection ◽  
Scheduling Model ◽  
Third Stage ◽  
Actual Flow ◽  
Batch Processors

Purpose: This research develops a batch scheduling model for a three-stage flow shop with job processors in the first and second stages and a batch processor in the third stage. The model integrates production process activities and a product inspection activity to minimize the expected total actual flow time.Design/methodology/approach: The problem of batch scheduling for a three-stage flow shop is formulated as a mathematical model, and a heuristic algorithm is proposed to solve the problem. This model applies backward scheduling to accommodate the objective of minimizing the expected total actual flow time.Findings: This research has proposed a batch scheduling model for a three-stage flow shop with job and batch processors to produce multiple items and an algorithm to solve the model. The objective is to minimize total actual time. The resulting production batches can be sequenced between all types of products to minimize idle time, and the batch processor capacity affects the sample size and indirectly affects the production batch size.Originality/value: This research develops a batch scheduling model for a three-stage flow shop constituting job and batch processors and carrying out integrated production and inspection activities to minimize the expected total actual flow time

scholarly journals Multi-items Batch Scheduling Model for a Batch Processor to Minimize Total Actual Flow Time of Parts through the Shop

2018 ◽  
Vol 20 (1) ◽  
pp. 73-88
Author(s):  
Nita P.A Hidayat ◽  
Andi Cakravastia ◽  
T.M.A Ari Samadhi ◽  
Abdul Hakim Halim
Keyword(s):  
Flow Time ◽  
Batch Scheduling ◽  
Scheduling Problem ◽  
Metal Working ◽  
Due Dates ◽  
Due Date ◽  
Batch Processor ◽  
Scheduling Model ◽  
Actual Flow

This study is inspired by a batch scheduling problem in metal working industry which guarantees to satisfy a due date as a commitment to customers. Actual flowtime adopts the backward scheduling approach and considers the due date. Using the actual flowtime as the objective means that the solution  is oriented to satisfy the due date, and simultaneosly to minimize the length of time of the parts spending in the shop. This research is to address a problem of scheduling batches consisting of multiple items of parts processed on a batch processor where the completed parts must be delivered several time at different due dates. We propose an algorithm to solve the problem.

scholarly journals A flow shop batch scheduling and operator assignment model with time-changing effects of learning and forgetting to minimize total actual flow time

2020 ◽  
Vol 13 (3) ◽  
pp. 546
Author(s):  
Dwi Kurniawan ◽  
Andi Cakravastia Raja ◽  
Suprayogi Suprayogi ◽  
Abdul Hakim Halim
Keyword(s):  
Flow Shop ◽  
Optimal Number ◽  
Batch Scheduling ◽  
Due Date ◽  
Processing Times ◽  
Actual Flow ◽  
Stage System ◽  
The Difference ◽  
Set Up ◽  
Operator Assignment

Purpose: This paper aims to investigate simultaneous problems of batch scheduling and operator assignment with time-changing effects caused by learning and forgetting.Design/methodology/approach: A number of parts will be processed in batches, each of which will be processed through a number of operations where there are alternative operators for each operation bringing different set up and processing times as operators experience different degree of learning and forgetting. A mathematical model is developed for the problems, and the decision variables are operator assignment, the number of batches, batch sizes and the schedule of the resulting batches. A proposed algorithm works by trying different number of batches, starting from one, and increasing the number of batches one by one until the objective function value does not improve anymore.Findings: We show both mathematically and numerically that the closest batch to the due date always becomes the largest batch in the schedule, and the faster operators learn, the larger the difference between the closest batch to the due date and the other batches, the lower optimal number of batches, and the lower the total actual flow time.Originality/value: Previous papers have considered the existence of alternative operators but have not considered learning and forgetting, or have considered learning and forgetting but only in a single-stage system and without considering alternative operators.

scholarly journals Integer Batch Scheduling Problems for a Single-Machine to Minimize Total Actual Flow Time

2015 ◽  
Vol 2 ◽  
pp. 118-123 ◽  
Author(s):  
Rinto Yusriski ◽  
Budi Astuti ◽  
Sukoyo ◽  
T.M.A. Ari Samadhi ◽  
Abdul Hakim Halim
Keyword(s):  
Single Machine ◽  
Flow Time ◽  
Batch Scheduling ◽  
Scheduling Problems ◽  
Actual Flow

A batch scheduling model formheterogeneous batch processor

2015 ◽  
Vol 54 (4) ◽  
pp. 1170-1185 ◽  
Author(s):  
Nita P.A. Hidayat ◽  
Andi Cakravastia ◽  
T.M.A. Ari Samadhi ◽  
Abdul Hakim Halim
Keyword(s):  
Batch Scheduling ◽  
Batch Processor ◽  
Scheduling Model

scholarly journals A single machine multi-job integer batch scheduling problem with multi due date to minimize total actual flow time

2021 ◽  
Vol 10 (3) ◽  
pp. 231-240
Author(s):  
Rinto Yusriski ◽  
Budi Astuti ◽  
Damawijaya Biksono ◽  
Tika Ayu Wardani
Keyword(s):  
Single Machine ◽  
Flow Time ◽  
Batch Scheduling ◽  
Batch Size ◽  
Simple Problem ◽  
Scheduling Problem ◽  
Due Dates ◽  
Due Date ◽  
Numerical Experience ◽  
Actual Flow

This research deals with a multi-job Integer batch scheduling problem on a single machine with different due dates. Every job demanded one or more parts, and the single machine processed the job into a number of batches. The objective is to minimize total actual flow time, defined as the total flow time of all jobs starting from the arrival to the common due date. The decisions are to determine the sequence of jobs, the number of batches, batch size, and sequence of all batches on a single machine. This research proposes three algorithms, developed based on the longest due date rule (The P1-LDD Algorithm), the adjacent pairwise interchange method (The P2-API Algorithm), and the permutation method (The P3-PM Algorithm). The numerical experience shows that the three algorithms produce an outstanding solution. The P1-LDD Algorithm fits to solve a simple problem. The P2-API Algorithm has superior to solve a big complicated problem. The P3-PM Algorithm has the best performance to solve small complicated problems.

A multi due date batch scheduling model on dynamic flow shop to minimize total production cost

2016 ◽  
Vol 9 ◽  
pp. 315-324 ◽  
Author(s):  
Tengku Nurainun ◽  
Ahmad Fudholi ◽  
Misra Hartati ◽  
Rado Yendra ◽  
Ismu Kusumanto
Keyword(s):  
Production Cost ◽  
Flow Shop ◽  
Batch Scheduling ◽  
Total Production ◽  
Dynamic Flow ◽  
Due Date ◽  
Scheduling Model

An Efficient Batch Scheduling Model for Hospital Sterilization Services Using Genetic Algorithm

2018 ◽  
Vol 9 (1) ◽  
pp. 1-17
Author(s):  
Shubin Xu ◽  
John Wang
Keyword(s):  
Genetic Algorithm ◽  
Medical Devices ◽  
Programming Model ◽  
Flow Time ◽  
Nonlinear Integer Programming ◽  
Batch Scheduling ◽  
Work In Process ◽  
Scheduling Model ◽  
Completion Times ◽  
Sum Of Completion Times

A major challenge faced by hospitals is to provide efficient medical services. The problem studied in this article is motivated by the hospital sterilization services where the washing step generally constitutes a bottleneck in the sterilization services. Therefore, an efficient scheduling of the washing operations to reduce flow time and work-in-process inventories is of great concern to management. In the washing step, different sets of reusable medical devices may be washed together as long as the washer capacity is not exceeded. Thus, the washing step is modeled as a batch scheduling problem where washers have nonidentical capacities and reusable medical device sets have different sizes and different ready times. The objective is to minimize the sum of completion times for washing operations. The problem is first formulated as a nonlinear integer programming model. Given that this problem is NP-hard, a genetic algorithm is then proposed to heuristically solve the problem. Computational experiments show that the proposed algorithm is capable of consistently obtaining high-quality solutions in short computation times.

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