With the continuous development of technology,traditional manual work has been becoming more and more automated.Most large or medium-sized companies have applied Enterprise Resource Planning(ERP)software into their bu...With the continuous development of technology,traditional manual work has been becoming more and more automated.Most large or medium-sized companies have applied Enterprise Resource Planning(ERP)software into their business and production activities.However,since many small firms cannot afford ERP because of its expensive cost,they often still employ manual work for the same tasks this software resolves,especially for scheduling.This paper aims to provide a possible solution for small businesses to try automated scheduling and discover whether it can help much.There are two main ways to make this determination:a mathematical model and a heuristic model,which are suitable for assessing low-and medium-sized workloads,respectively.This case study was carried out in a small domestic interior furniture company,particularly in scheduling for their customized products in two-stage flow shop.Normally,they produce according to the sequence of customers’orders.However,when we applied these supportive tools with batch-processing machines,they experienced enhanced production performance due to diminishing setup time for distinctive items and a more streamlined arrangement of job sequences.These changes were implemented for some small companies that do not use many production stages and have a suitable number of jobs and customers.If this method were applied to larger demands,it would need further improvement and development to become a complete tool that can perform like a part of an ERP system.展开更多
Production scheduling involves all activities of building production schedules,including coordinating and assigning activities to each person,group of people,or machine and arranging work orders in each workplace.Prod...Production scheduling involves all activities of building production schedules,including coordinating and assigning activities to each person,group of people,or machine and arranging work orders in each workplace.Production scheduling must solve all problems such as minimizing customer wait time,storage costs,and production time;and effectively using the enterprise’s human resources.This paper studies the application of flexible job shop modelling on scheduling a woven labelling process.The labelling process includes several steps which are handled in different work-stations.Each workstation is also comprised of several identical parallel machines.In this study,job splitting is allowed so that the power of work stations can be utilized better.The final objective is to minimize the total completion time of all jobs.The results show a significant improvement since the new planning may save more than 60%of lead time compared to the current schedule.The contribution of this research is to propose a flexible job shop model for scheduling a woven labelling process.The proposed approach can also be applied to support complex production scheduling processes under fuzzy environments in different industries.A practical case study demonstrates the effectiveness of the proposed model.展开更多
In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This resear...In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison.The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders.This study analyzes the flexible flow shop scheduling problem with a sequence dependent setup by modifying the processing time and setup time to minimize the makespan on multiple machines.Based on the defined mathematical model,this study includes an alternative approach and application of heuristic algorithm with the input being big data.Both optimization programs are used in this study and compared to determine which method can better solve the company’s problems.The proposed algorithm is able to improve machine utilization with large-scale problems.展开更多
文摘With the continuous development of technology,traditional manual work has been becoming more and more automated.Most large or medium-sized companies have applied Enterprise Resource Planning(ERP)software into their business and production activities.However,since many small firms cannot afford ERP because of its expensive cost,they often still employ manual work for the same tasks this software resolves,especially for scheduling.This paper aims to provide a possible solution for small businesses to try automated scheduling and discover whether it can help much.There are two main ways to make this determination:a mathematical model and a heuristic model,which are suitable for assessing low-and medium-sized workloads,respectively.This case study was carried out in a small domestic interior furniture company,particularly in scheduling for their customized products in two-stage flow shop.Normally,they produce according to the sequence of customers’orders.However,when we applied these supportive tools with batch-processing machines,they experienced enhanced production performance due to diminishing setup time for distinctive items and a more streamlined arrangement of job sequences.These changes were implemented for some small companies that do not use many production stages and have a suitable number of jobs and customers.If this method were applied to larger demands,it would need further improvement and development to become a complete tool that can perform like a part of an ERP system.
基金This research was partly supported by the National Kaohsiung University of Science and Technology,and MOST 109-2622-E-992-026 from the Ministry of Sciences and Technology in Taiwan。
文摘Production scheduling involves all activities of building production schedules,including coordinating and assigning activities to each person,group of people,or machine and arranging work orders in each workplace.Production scheduling must solve all problems such as minimizing customer wait time,storage costs,and production time;and effectively using the enterprise’s human resources.This paper studies the application of flexible job shop modelling on scheduling a woven labelling process.The labelling process includes several steps which are handled in different work-stations.Each workstation is also comprised of several identical parallel machines.In this study,job splitting is allowed so that the power of work stations can be utilized better.The final objective is to minimize the total completion time of all jobs.The results show a significant improvement since the new planning may save more than 60%of lead time compared to the current schedule.The contribution of this research is to propose a flexible job shop model for scheduling a woven labelling process.The proposed approach can also be applied to support complex production scheduling processes under fuzzy environments in different industries.A practical case study demonstrates the effectiveness of the proposed model.
文摘In the competitive global marketplace,production scheduling plays a vital role in planning in manufacturing.Scheduling deals directly with the time to output products quickly and with a low production cost.This research examines case study of a Radio-Frequency Identification labeling department at Avery Dennison.The main objective of the company is to have a method that allows for the sequencing and scheduling of a set of jobs so it can be completed on or before the customer’s due date to minimize the number of late orders.This study analyzes the flexible flow shop scheduling problem with a sequence dependent setup by modifying the processing time and setup time to minimize the makespan on multiple machines.Based on the defined mathematical model,this study includes an alternative approach and application of heuristic algorithm with the input being big data.Both optimization programs are used in this study and compared to determine which method can better solve the company’s problems.The proposed algorithm is able to improve machine utilization with large-scale problems.
