Real Job Shop Research Articles

An efficient approach for solving a job shop scheduling problem with resources constraints: a case study iCIM 3000

In this work, we are interested in a job shop scheduling problem (JSSP) with resources availability constraints. The aim consists in scheduling a set of N jobs on M machines. To be processed in the system, each job needs an number of consumable resources that are available in a limited quantity. Solving such a problem means finding better jobs sequencing in order to minimise the maximum execution time. We suggest two different methods to solve the above-mentioned problem. We firstly propose a set of four heuristics based on priority rules. Then, we make call to genetic algorithm. Using a real job shop manufacturing system data, a large-scale experiment was performed in order to analyse the performance of the proposed methods. The studied system is called iCIM 3000. The simulation results reveal that the new proposed heuristics are better than genetic algorithms and achieve to good solutions in shorter time.

Digital twin oriented multi-objective flexible job shop scheduling model and its hybrid particle swarm optimization

To solve the problems of low efficiency and insufficient dynamic response of job shop scheduling in the discrete manufacturing process, a multi-objective flexible job shop scheduling model for digital twin and its solution method are proposed. Firstly, a digital twin scheduling model with physical entity, virtual model and production plan is constructed, and four factors are taken as optimization goals. Then, a hybrid particle swarm optimization method is designed to increase the refined optimization ability, and the obtained Pareto optimal solution set is analyzed by grey relational analysis to obtain a satisfactory solution which coincides with the actual production. Finally, a three-dimensional model which is completely mapped with the real job shop scheduling is built by Plant Simulation software. The scheduling process is simulated and optimized by combining with the production data of an enterprise, which verifies the feasibility and applicability of this method, and will effectively guide the production practice.

Offline segmentation of spatio-temporal order trajectories by mixed-integer linear programming for determining process times in production systems

Real-time indoor positioning systems in manufacturing systems are used to track production orders. This generates spatio-temporal trajectories which can be segmented to determine process times. We present formulations of the offline segmentation problem as mixed-integer linear programs (MILPs) that utilize the sequence of processing steps from ERP systems. The MILP formulations are compared with online heuristics in terms of their accuracy and computational effort on data generated with features from a real job shop. We show that in terms of accuracy our offline segmentation formulations outperform the online heuristics with increasing measurement errors, justifying their higher computational effort.

Reliability evaluation and component importance measure for manufacturing systems based on failure losses

Little work has been done to assess the reliability of a vital system like the manufacturing system. In this article, a novel and effective system reliability evaluation method in terms of failure losses has been proposed for manufacturing systems of job shop type, and then the failure losses based component importance measure (CIM) is used for importance analysis of equipment. The former indicates the present system reliability situation and the latter points the way to reliability improvement efforts. In this scheme, the problem is described and modeled by a dynamic directed network. Consider that the actual processing time of machines is to contribute to failure occurrence, it is used to calculate the failure times and failure losses. The obtained total failure times and failure losses of the system are applied to evaluate its reliability. Techniques to estimate two kinds of failure losses based CIMs are presented. They offer guidelines to realize system reliability growth cost-effectively. A case study of a real job shop is provided as an example to demonstrate the validity of the proposed methods. Comparison to other commonly used methods shows the efficiency of the proposed methods.

Applying Bond Graphs for Modelling the Manufacturing Dynamics

Supply chain dynamics and execution control seem not to receive as much attention as the domain of supply chain planning by means of static optimization models. The dynamics of manufacturing systems also deserves attention, since they are the fundamental pieces of a supply chain. In this paper, a dynamic model for the production control of a multi-product manufacturing system is developed using the Bond Graph modeling methodology. The proposed model is applied to depict the dynamics of a real job shop production system of propylene bags, where the control objective is to adjust the processing frequency of the machines to attend the demands of the products, while keeping the work in process at the desired levels. Exploratory simulations were carried out, and the preliminary results showed that the system could be autonomously controlled. Some advantages of the Bond Graph methodology are also highlighted.

An Artificial Immune Systems (AIS)-based Unified Framework for General Job Shop Scheduling

Process scheduling is a classical problem in the field of production planning and control; in particular, effective job shop scheduling remains an essential component in today's highly dynamic and agile production environment. This paper presents unified framework for solving generic job shop scheduling problems based on the formulation of a job shop into three main classes of problem, namely, static, semi-dynamic and dynamic scheduling problems. Algorithms based on artificial immune systems, an engineering analogy of the human immune system, are developed to solve the respective classes of job shop scheduling problems. A high level decision support model is presented for the effective deployment of the scheduling strategies whereby a unified approach to solving real job shop problems is achieved.

Research on Dynamic Job Shop Scheduling Problem Base on Hybrid Genetic Algorithm

In real production processing, job shop scheduling problem (JSP) is often express as dynamic scheduling problem. In this article a hybrid genetic algorithm and handling strategies are used for real job shop scheduling problem. It gives the scheduling result with the appropriate handling strategies to the stochastic events such as equipment breakdown and urgent orders. The data of Shanghai Shen Mo Die & Mold Manufacturing Co., Ltd (ShenMo) is used for the application of dynamic scheduling simulation, and the results of which show that the proposed method can satisfactorily solve the stochastic events of scheduling.

Modelling randomness of a manual assembly system with walking workers

Most proposed approaches for modelling and simulation of an assembly production line have focused on conventional assembly lines where one (or more) stationary worker stays at a given station to complete a repetitive assembly operation and when this operation is accomplished, the assembled part is transferred to another worker at the next station for the next assembly operation. This paper presents an investigation of a linear walking worker assembly line where one worker walks along the line to complete the assembly of a product from start to finish. The study was carried out based on a real job shop environment with a demand-pull production control system. The randomness of walking worker activities was modelled using a proprietary simulation package. The paper discusses several issues which may assist in the early stages of designing a linear walking worker line.

The relative contributions of input and output controls on the performance of a workload control system in Make-To-Order companies

Workload control (WLC) systems can be seen as a natural extension of input-output control systems which allow both the control of jobs into the shop and the control of capacity which affects the flow of finished goods out of the shop. In previous research, it has been shown that WLC can help to reduce manufacturing lead times, even if the total workload processed by the shop in a given time period is maintained at a constant rate. However, the relative contributions of the input control mechanisms versus the output control mechanisms have not been clearly determined. This paper seeks to explore this which affects the flow of finished goods out of the shop. In previous research, it has been shown that WLC can help to reduce manufacturing lead times, even if the total workload processed by the shop in a given time period is maintained at a constant rate. However, the relative contributions of the input control mechanisms versus the output control mechanisms have not been clearly determined. This paper seeks to explore this issue using a simulation of a real job shop, in which the WLC system that has been developed at Lancaster University is used. It explores the use of input control alone and the use of input control plus output control. In addition, the relation between workload and various performance measures, such as lead time, queueing time and capacity utilisation, is explored. The results of the experiments show that one should consider input control and output control as two levers of control that are both to be pulled rather than relying on the single lever of stopping the input when the WIP reaches some preset level.

Dynamic scheduling of manufacturing job shops using extreme value theory

Most job shop scheduling approaches reported in the literature assume that the scheduling problem is static (i.e. job arrivals and the breakdowns of machines are neglected) and in addition, these scheduling approaches may not address multiple criteria scheduling or accommodate alternate resources to process a job operation. In this paper, a scheduling method based on extreme value theory (SEVAT) is developed and addresses all the shortcomings mentioned above. The SEVAT approach creates a statistical profile of schedules through random sampling, and predicts the quality or 'potential' of a feasible schedule. A dynamic scheduling problem was designed to reflect a real job shop scheduling environment closely. Two performance measures, viz. mean job tardiness and mean job cost, were used to demonstrate multiple criteria scheduling. Three factors were identified, and varied between two levels each, thereby spanning a varied job shop environment. The results of this extensive simulation study show that the SEVAT scheduling approach produces a better performance compared to several common dispatching rules.

The time spent in a dynamic job shop

An open queuing network model of dynamic job shops is considered here. Approximations for the time spent by a job in the job shop are derived. The accuracy of these approximations are demonstrated by comparing these approximate results to simulation results for some symmetric job shops and flow shops. These approximations are simple enough to be implemented on a personal computer and can be applied to any real job shop with local scheduling disciplines.

A model to examine the effect of loading conditions on scheduling rules in a job shop environment

Abstract Although a great deal of research has been carried out in the field of job scheduling this has generally been directed towards examining the benefits of particular rules and presenting improved algorithms. This paper examines how real job shop problems can be modelled and available scheduling rules examined for particular capacity loading conditions. A model of a medium-size production job shop is developed and it is shown that, for their particular shop layout and job mix, the performance and ranking of particular rules with respect to certain criteria, change with shop conditions. The model developed can easily be applied to a wide range of job shop situations and once performance charts have been produced for those scheduling rules available, they can be used to aid the existing scheduling system whether manual or computer based.