Percentage Of Tardy Jobs Research Articles

Defining accurate delivery dates in make to order job-shops managed by workload control

Workload control (WLC) is a lean oriented system that reduces queues and waiting times, by imposing a cap to the workload released to the shop floor. Unfortunately, WLC performance does not systematically outperform that of push operating systems, with undersaturated utilizations levels and optimized dispatching rules. To address this issue, many scientific works made use of complex job-release mechanisms and sophisticated dispatching rules, but this makes WLC too complicated for industrial applications. So, in this study, we propose a complementary approach. At first, to reduce queuing time variability, we introduce a simple WLC system; next we integrate it with a predictive tool that, based on the system state, can accurately forecast the total time needed to manufacture and deliver a job. Due to the non-linearity among dependent and independent variables, forecasts are made using a multi-layer-perceptron; yet, to have a comparison, the effectiveness of both linear and non-linear multi regression model has been tested too. Anyhow, if due dates are endogenous (i.e. set by the manufacturer), they can be directly bound to this internal estimate. Conversely, if they are exogenous (i.e. set by the customer), this approach may not be enough to minimize the percentage of tardy jobs. So, we also propose a negotiation scheme, which can be used to extend exogenous due dates considered too tight, with respect to the internal estimate. This is the main contribution of the paper, as it makes the forecasting approach truly useful in many industrial applications. To test our approach, we simulated a 6-machines job-shop controlled with WLC and equipped with the proposed forecasting system. Obtained performances, namely WIP levels, percentage of tardy jobs and negotiated due dates, were compared with those of a set classical benchmark, and demonstrated the robustness and the quality of our approach, which ensures minimal delays.

A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints

This paper considers a simulation-based analysis of dispatching rules for scheduling in a dynamic job shop with batch release taking into account the extended technical precedence constraint which is a new term defined as the extension of conventional routing-based technical precedence constraint in our paper. With respect to tardiness-related measures, the relative performances of some widely-used dispatching rules as well as four new ones proposed in our paper are evaluated for different settings of the model parameters. The results of the simulation study demonstrate the effectiveness of the four new proposed dispatching rules, and also reveal that the relative performance of dispatching rules can be affected by some model parameters. For the standard job shop scheduling problem model, where there are no extended technical precedence constraints between jobs, as well as for the models taking into account the extended technical precedence constraint, it is shown that for minimizing the total tardiness and the percentage of tardy jobs, the four new proposed dispatching rules are very effective under relatively loose due date. With respect to tardiness-related objectives, the relative performance of the analyzed dispatching rules can be affected by changing not only the levels of the extended technical precedence constraint, but also the due date tightness.

Dynamic parallel machine scheduling with random breakdowns using the learning agent

Agent technology has been widely applied in the manufacturing process due to its flexibility, autonomy, and scalability. In this paper, the learning agent is proposed to solve a dynamic parallel machine scheduling problem which considers random breakdowns. The duty of the agent, which is based on the Q-learning algorithm, is to dynamically assign arriving jobs to idle machines according to the current state of its environment. A state-action table involving machine breakdowns is constructed to define the state of the agent's environment. Three rules, including SPT (Shortest Processing Time), EDD (Earliest Due Date) and FCFS (First Come First Served), are used as actions of the agent, and the e-greedy policy is adopted by the agent to select an action. In the simulation experiment, two different objectives, including minimising the maximum lateness and minimising the percentage of tardy jobs, are utilised to validate the ability of the learning agent. The results demonstrate that the proposed agent is suitable for the complex parallel machine environment.

Coping with finite storage space in job shops through order release control: an assessment by simulation

Most literature on job shops assumes that an infinite storage space is available on the shop floor. But in practice, storage space is limited or finite. The job shop control problem with finite storage space has received little attention; it is a complex problem for which optimised scheduling may lead to unfeasible and poor quality solutions. The alternative to a scheduling solution is the use of controlled order release. This study uses simulation to assess the performance of four order release control rules. Results indicate that the best results are achieved by the workload control order release (WLCOR) rule. This rule produces results comparable to the optimum solution identified by analytical modelling in terms of the storage space required to achieve a certain production rate. The advantage of WLCOR is that it does this while simultaneously controlling lead times and the percentage of tardy jobs. Results have significant implications for practice, particularly where space is at a premium.

Workload control and order release in two-level multi-stage job shops: an assessment by simulation

Most studies on the performance of workload control (WLC) order release methods assume products have simple structures. But, in practice, products are often complex and consist of a number of sub-assemblies that flow through a ‘level 1’ job shop before converging on several final assembly operations in a ‘level 2’ assembly shop. Evaluating the performance of release methods in this context – referred to as the ‘two-level multi-stage job shop’ – is an important step towards improving the alignment between WLC theory and practice. We use simulation to assess the performance of four of the best-performing WLC order release methods. Results suggest that WLC order release has the potential to limit work-in-process (WIP) while reducing the percentage of tardy jobs. It is also important to consider when and where release should be controlled. Results suggest that: (1) orders should be considered for release to level 2 when the first sub-assembly is complete, rather than only when all of the sub-assemblies that make up an assembly order are complete at level 1; and, (2) exercising control at level 2 (with or without control at level 1) leads to a greater reduction in the percentage of tardy jobs than control at level 1 only.

A Fuzzy Decision Support System for Selecting the Optimal Scheduling Rule in Robotic Flexible Assembly Cells

The aim of this paper is to present a proposed methodology to select optimal scheduling rule for robotic flexible assembly cells based fuzzy decision support system. Six common scheduling rules are considered, and three independent objectives, namely, the minimising of makespan (Cmax), total tardiness (TD) and percentage of tardy jobs (%T) are measured. A fuzzy decision support system is implemented using the Matlab fuzzy toolbox. The final results demonstrate the effectiveness of the proposed methodology to select optimal scheduling rule in a multi-product assembly environment.

Controlled order release: a performance assessment in job shops with sequence-dependent set-up times

Findings from recent implementations of Workload Control (WLC) have called for research to investigate how sequence-dependent set-up times can best be handled within the design of the concept. In response, this study assesses the performance of four of the best-performing release methods from the literature in a job shop with sequence-dependent set-up times by simulation. First, the four methods are compared without considering set-up requirements at release. Second, the methods are refined to consider set-up requirements before being compared against the original methods. A release method that combines continuous and periodic release emerges as the best-performing method. Findings further suggest that considering set-up requirements at release do not have a significant positive effect on performance and may even be counterproductive: conflicting goals between the selection rules employed at release and dispatching may lead to an increase in the percentage of tardy jobs. Future research should consider whether the results hold if set-up times are not distributed equally across job types and work centres.

The performance of combinatorial priority rules in a manufacturing flow shop

Some of the previous research indicates that no single priority rule could perform excellently on those common performance measures. This study focuses on evaluating the impact of deploying combinations of four single priority rules on a three-stage manufacturing flow shop, i.e., different rules are employed at different workstation. Full factorial combinations of four commonly used priority rules, leading to 64 rule combinations, are analysed. Besides, variations in buffer capacity and due date allowance are taken into account. Both terminating and non-terminating systems are investigated in this study. For terminating system, variations in production volume are also considered. Simulation experiments have been conducted and the performance of the combinations is analysed by monitoring four measures, namely: 1 mean lead time 2 mean tardiness 3 number of jobs completed 4 percentage of tardy jobs.

Development and analysis of scheduling decision rules for a dynamic flexible job shop production system: a simulation study

The present paper focuses on a simulation-based experimental study of scheduling decision rules for scheduling a typical dynamic flexible job shop production system. The case of partial flexibility is considered wherein an operation can be performed on three different machines. Each operation can be performed efficiently on the primary machine. The other two alternative machines are also capable of performing the same operation, though less efficiently. This is modelled as a percentage increase in the processing time when an operation is performed on an alternate machine. A discrete event simulation model of the job shop system is used as a test bed for experimentation. Three scheduling rules from the literature are used for machine selection decision. A total of 15 scheduling rules from the literature are incorporated in the simulation model for job scheduling decisions. Six new scheduling rules for job scheduling are also developed and investigated. The performance measures evaluated are the mean flow time, standard deviation of flow time, mean tardiness, standard deviation of tardiness and percentage of tardy jobs. The analysis of simulation results reveal that the proposed scheduling rules provide better overall performance for the various measures when compared with the existing scheduling rules.

Efficient jobshop dispatching rules: Further developments

Many dispatching rules for scheduling in dynamic jobshops have been proposed over many years. The research issues in jobshop scheduling seem to be still open in the sense that no single rule has been found to be the best under all shopfloor conditions even with respect to one single measure of performance. Added to this problem, there are several measures of performance, e.g. the minimizations of mean, maximum and variance of flowtime, percentage of tardy jobs, and mean, maximum and variance of tardiness of jobs. Recent studies have reported the development of more efficient dispatching rules than the popular rules, e.g. SPT, COVERT, MOD and ATC. This study is an attempt to improve some of the recently reported dispatching rules. An extensive simulation study reveals that the improved rules developed in the present study appear to be quite effective in minimizing mean flowtime, and maximum tardiness and variance of tardiness of jobs.

Simultaneous versus sequential scheduling of multiple resources which constrain system throughput

The GOAL SYSTEMTM implements a drum-buffer-rope (DBR) approach to production scheduling. Earlier versions of the software were only capable of building a schedule for one constrained resource at a time. If multiple resources constrained the overall system's capability, the schedules for these resources had to be created sequentially. However, the current version contains an ability to simultaneously create multiple constraint schedules. A set of solutions was generated for benchmark problems developed in previous research. The new results were compared to solutions produced by the sequential algorithm, as well as solutions which optimally minimize maximum tardiness. The simultaneous algorithm was found to slightly reduce maximum tardiness, but performed worse with respect to average flow-time, percentage of tardy jobs and total days late.

A simulation study for dynamic scheduling in a hybrid assembly/job shop considering the JIT context

This paper is a report of a simulation study that investigates a dynamic approach to scheduling jobs in a hybrid assembly/job shop, with special application to welding shop operations. Both JIT arrival and JIT delivery are considered. Various dispatching rules with different utilization are tested for the following performance measures; mean flow time, percentage of tardy jobs, mean tardiness, sum of mean tardiness and mean earliness. The results indicate that the SPT rule is the best for the mean flow time. The MSLACK rule, that we suggest in this paper, is the best for mean tardiness, the sum of mean tardiness and mean earliness. However, it is not clear which rule is the best for the percentage of tardy jobs. We also investigate the effect of changing the release time on the performance measure.

Design of efficient job shop scheduling rules

This paper considers the design and simulation-based analysis of dispatching rules for scheduling in dynamic job shops. Based upon the combination of well-known rules new scheduling rules are developed. For evaluating the relative performance of the dispatching rules the criteria of mean and maximum flowtime, variance of flowtime, mean and maximum tardiness, percentage of tardy jobs and variance of tardiness have been chosen. The results of the simulation study reveal that the simple structured combination rules are quite efficient.

Simple priority rule combinations: An approach to improve both flow time and tardiness

Prior research indicates that no single priority rule displays superior performance on both flow time and tardiness measures. While the 'shortest processing time' rule does minimize the mean flow time, it performs poorly on the tardiness criterion. This study focuses on the same issue, whether both tardiness and flow time measures can be improved at the same time by combining simple priority rules. A total of 64 combination rules were developed by concurrently deploying four simple priority rules in all possible combinations in a simulated, three-stage serial manufacturing shop. The performance of the combinations was analysed and compared using three criteria, the mean flow time, mean tardiness, and the percentage of tardy jobs, under two shop load conditions. The results indicate that combinations using the 'shortest processing time' and 'earliest due date' rules produce excellent results on both tardiness and percentage of tardy jobs criteria without substantially sacrificing flow time. In addition, the shop load factor appears to have little effect upon the performance of these combinations.

A Simulation Study of Due-date Assignment Rules in a Dynamic Job Shop

This paper is a report of a simulation study that investigates a dynamic approach to scheduling jobs in a multi-machine job shop. The workload information of a job is used in different forms to evaluate the shop performance based on three measures: mean job lateness, percentage of tardy jobs and lateness variance. Different combinations of due-date assignment methods and sequencing rules are compared based on specific performance criteria. The results indicate that using the cumulative distribution function of workload information can yield a better performance than using a proportional function of workload information or ignoring shop congestion information. A few situations are identified in which workload information is not critical.