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

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.

Cost Optimization Problem of Hybrid Flow-Shop Based on PSO Algorithm

2012 ◽  
Vol 532-533 ◽  
pp. 1616-1620 ◽  
Author(s):  
Zhong Hua Han ◽  
Xiao Fu Ma ◽  
Li Li Yao ◽  
Hai Bo Shi
Keyword(s):  
Production Cost ◽  
Job Scheduling ◽  
Flow Shop ◽  
Cost Optimization ◽  
Task Assignment ◽  
Pso Algorithm ◽  
Hybrid Flow Shop ◽  
Total Production ◽  
Process Route ◽  
Processing Cost

A PSO-algorithm-based job scheduling method that takes production cost as optimization object is presented in this paper. The cost optimization model of HFSP, in which production cost is considered as an optimal factor, is constructed. PSO is used to take global optimization, make the production task assignment and find which machine the jobs should be assigned at each stage, which is also called the process route of the job. After that the local assignment rules are used to determine the job’s starting time and processing sequence at each stage. The total production cost converted by time-based scheduling results is comprehensively considering the processing cost, waiting costs, and the products storage costs. The numerical results show the effectiveness of the algorithm after comparing between multi-group programs.

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 Minimizing Total Production Cost in a Hybrid Flow Shop: a Simulation-Optimization Approach

2020 ◽  
Vol 19 (4) ◽  
pp. 559-570
Author(s):  
D. Istokovic ◽  
M. Perinic ◽  
M. Vlatkovic ◽  
M. Brezocnik
Keyword(s):  
Flow Shop ◽  
Simulation Optimization ◽  
Simulation Software ◽  
Production Costs ◽  
Batch Scheduling ◽  
Hybrid Flow Shop ◽  
Optimization Approach ◽  
Total Production ◽  
Manufacturing Companies ◽  
Dependent Setup Times

To ensure the competitiveness of manufacturing companies in the market, batching and batch scheduling are among the most important tasks. This paper presents a simulation-optimization approach that combines the discrete event simulation (DES) and the genetic algorithm (GA) to solve the batching and batch scheduling problem in a hybrid flow shop (HFS). HFS is widely used for the production of medium and large quantities of different technologically complex products. Based on a real-world manufacturing company, the HFS simulation model was developed using the Tecnomatix Plant Simulation software package. By analysing the influencing factors that represent production costs, a new formulation of the total cost of production was proposed. The purpose of this case study was to ensure timely delivery and minimize production costs by integrating simulation and optimization tools. This research considers sequence-dependent setup times, and availability of manufacturing and transportation equipment. The results of this research showed that the proposed simulation-optimization approach can be applied to solve the problem in many industrial case studies.

Immaterial Cost and Production: Maximum Production Cost Level Through Marginal Approach

2020 ◽  
Vol 8 (2) ◽  
pp. 128-149
Author(s):  
Dini Maulana Lestari
Keyword(s):  
Quantitative Study ◽  
Marginal Cost ◽  
Production Cost ◽  
Maximum Level ◽  
Production Costs ◽  
Total Production ◽  
Sugar Factory ◽  
Maximum Production ◽  
Cost Approach ◽  
South Sulawesi

This paper will discuss about the immaterial costs and production yields at one of the refined sugar factory companies in Makassar, South Sulawesi. The theory is based on the fact that Immaterial is a cost that is almsgiving, meaning costs that are outside of the basic costs of the company in producing production, so this research aims to find out: (1) what is the production cost needed to produce this production, (2) the maximum level of production at company from 2013 to 2017. This type of research is a quantitative study because it uses a questionnaire in the form of values ​​that are processed using the marginal cost approach formula. The results of the analysis show that (1) the maximum level of production costs occurred in 2016 amounting to 6,912 with an Immaterial cost of Rp. 2,481,796,800 and the total production produced is 359,077.3 tons (2) The required workforce with the total production produced is 359,077.3 tones of 180 people including the maximum production point which means that the lowest value is achieved (optimal).    

MINIMALISASI BIAYA SIMPAN DAN BIAYA SETUP PADA MULTIPLE PRODUK: SIMULASI DENGAN CAPACITATED LOT SIZING PROBLEM

2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma
Keyword(s):  
Production Cost ◽  
Lot Sizing ◽  
Setup Time ◽  
Production Costs ◽  
Total Production ◽  
Product Cycle ◽  
Lot Size ◽  
Setup Costs ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.

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