Abstract: Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure.
Abstract: This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.
Abstract: In this paper, we introduce a flexible box erecting
machine (BEM) that swiftly and automatically transforms cardboard
into a three dimensional box. Recently, the parcel service and
home-shopping industries have grown rapidly, and there is an
increasing need for various box types to ship various products.
However, workers cannot fold thousands of boxes manually in a day.
As such, automatic BEMs are garnering greater attention. This study
takes equipment operation into consideration as well as mechanical
improvements in order to design a BEM that is able to outperform its
conventional counterparts. We analyzed six dispatching rules – First In
First Out (FIFO), Shortest Processing Time (SPT), Earliest Due Date
(EDD), Setup Avoidance, EDD + SPT, and EDD + Setup Avoidance –
to determine which one was most suitable for BEM operation.
Consequently, SPT and Setup Avoidance were found to be the most
critical rules, followed by EDD + Setup Avoidance, EDD + SPT,
EDD, and FIFO. This hierarchy was valid for both our conventional
BEM and our new flexible BEM from the viewpoint of processing
time. We believe that this research can contribute to flexible BEM
management, which has the potential to increase productivity and
convenience.
Abstract: In this paper, multi-processors job shop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. By using the suitable hybrid of priority dispatching rules, the process of finding the best solution will be improved. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. Thus, the similar work has the same production lines. Other advantage of this algorithm is that the similar machines (not the same) can be considered. So, these machines are able to process a job with different processing and setup times. According to this capability and from this algorithm evaluation point of view, a number of test problems are solved and the associated results are analyzed. The results show a significant decrease in throughput time. It also shows that, this algorithm is able to recognize the bottleneck machine and to schedule jobs in an efficient way.
Abstract: The process of wafer fabrication is arguably the most
technologically complex and capital intensive stage in semiconductor
manufacturing. This large-scale discrete-event process is highly reentrant,
and involves hundreds of machines, restrictions, and
processing steps. Therefore, production control of wafer fabrication
facilities (fab), specifically scheduling, is one of the most challenging
problems that this industry faces. Dispatching rules have been
extensively applied to the scheduling problems in semiconductor
manufacturing. Moreover, lot release policies are commonly used in
this manufacturing setting to further improve the performance of such
systems and reduce its inherent variability. In this work, simulation is
used in the scheduling of re-entrant flow shop manufacturing systems
with an application in semiconductor wafer fabrication; where, a
simulation model has been developed for the Intel Five-Machine Six
Step Mini-Fab using the ExtendTM simulation environment. The
Mini-Fab has been selected as it captures the challenges involved in
scheduling the highly re-entrant semiconductor manufacturing lines.
A number of scenarios have been developed and have been used to
evaluate the effect of different dispatching rules and lot release
policies on the selected performance measures. Results of simulation
showed that the performance of the Mini-Fab can be drastically
improved using a combination of dispatching rules and lot release
policy.
Abstract: Grid computing is growing rapidly in the distributed
heterogeneous systems for utilizing and sharing large-scale resources
to solve complex scientific problems. Scheduling is the most recent
topic used to achieve high performance in grid environments. It aims
to find a suitable allocation of resources for each job. A typical
problem which arises during this task is the decision of scheduling. It
is about an effective utilization of processor to minimize tardiness
time of a job, when it is being scheduled. This paper, therefore,
addresses the problem by developing a general framework of grid
scheduling using dynamic information and an ant colony
optimization algorithm to improve the decision of scheduling. The
performance of various dispatching rules such as First Come First
Served (FCFS), Earliest Due Date (EDD), Earliest Release Date
(ERD), and an Ant Colony Optimization (ACO) are compared.
Moreover, the benefit of using an Ant Colony Optimization for
performance improvement of the grid Scheduling is also discussed. It
is found that the scheduling system using an Ant Colony
Optimization algorithm can efficiently and effectively allocate jobs
to proper resources.