Pure Flow Shop Research Articles

Heterogeneous worker multi-functionality and efficiency in dual resource constrained manufacturing lines: an assessment by simulation

Flexibility is a main mean to create resilient supply chains. The most flexible resources are often human resources but creating high, homogenous skill levels is not cost efficient. Heterogenous labour provides an alternative. The literature on Dual Resource Constrained (DRC) shops modelled heterogeneous labour with multi-functionality and efficiency matrices that indicate if a worker can perform at a station and according to which level of efficiency. However, this literature typically considered these matrices as a given environmental factor rather than a factor under firm control. Consequently, it typically neglected literature that can be used to guide matrix design. In response, this study draws on the literature on unbalanced lines to test eight different matrices to guide worker training. Discrete event simulation is then used to evaluate their performance in a DRC pure flow shop with high variability in demand and processing times. Results demonstrate that the matrix design impacts performance and that an unbalanced design has the potential to improve performance compared to a balanced design and full multi-functionality. Specifically, the bowl configuration shows much promise, which further confirms the “bowl phenomenon”. However, performance gains are dependent on the combination of When, Where and Who rules used to guide the worker assignment decision. So, the decision on worker training is also contingent on the decision which worker assignment rule to use. Findings have important implications for research and practice, providing guidance on how to design more resilient shops and supply chains.

A Study of Sequencing Rules in a Dynamic Pure Flow Shop.(Dept.M)

A Study of Sequencing Rules in a Dynamic Pure Flow Shop.(Dept.M)

Order review and release in make-to-order flow shops: analysis and design of new methods

Increased customization has strengthened the importance of make-to-order companies. The advent of lean management and the introduction of smart and flexible technologies has enabled many of these companies to create flow shop routings. Order review and release (ORR) research, which originally focused on job shops, has started paying attention to flow shops. However, the results have not provided clarity on the best ORR method for flow shops. This study aims at developing such a method by applying a modular design approach. It identifies the relevant elements of ORR methods for flow shops, combines them into new methods and evaluates them in a simulation study. The simulation results demonstrate that performance in pure flow shops can be strongly improved by applying the right combination of workload measures, load balancing, and order dispatching. Specifically, the results show that (1) classical workload measures are still as effective as novel measures that have been suggested for flow shops, (2) balancing workloads explicitly through optimization at the order release stage strongly improves performance, and (3) shortest processing time dispatching is highly effective in flow shops as it avoids starvation of stations. In-depth analyses have been executed to unravel the reasons of performance improvements. As such, the article provides clarity on the improvement potential that is available for ORR in flow shops, while the new modular methods provide a first step in exploiting this potential.

Comparing heuristic methods’ performance for pure flow shop scheduling under certainand uncertain demand

Comparing heuristic methods’ performance for pure flow shop scheduling under certainand uncertain demand

Sistem Optimasi Penjadwalan Mesin Produksi Menggunakan Metode GUPTA Berbasis Android

Research has been carried out by developing an optimization information system for scheduling production machines by applying the Android-based GUPTA method. This android-based application is able to optimize production time, because in the android application it implements the GUPTA algorithm which uses the calculation of the comparative processing time on every machine in the company by prioritizing the smallest processing time for scheduling which aims to optimize production scheduling time, by paying attention to the value of makespan to produce product size 12 griddle, size 14 griddle, 16 size griddle, 18 size griddle and 20 size griddle so that an optimal makespan value is obtained. The GUPTA method can be used in problems with more than two machines, because this method combines the time of each process on the first and subsequent machines to find the minimum value and can only be used in pure flow shop scheduling. The advantage of this method is that it determines scheduling only on one machine group. This research resulted in an Android-based application that can schedule products to be produced by machines automatically. From the results of testing with a total of 12 pieces of production in each product with a total of 5 different sizes, the minimum value of makespan is obtained, namely 2054569 minutes with the sequence of product processing with work order 12 griddle, griddle 18, griddle 20, griddle 16, and griddle 14 The accuracy of the application test results shows 98.87% for the first time and 98.84% for the second time when compared with manual calculations.

Workload Control order release in general and pure flow shops with limited buffer size induced blocking: an assessment by simulation

Most manufacturing shops in practice have limited physical space in front of each workstation, due, for example, to physical, economical or operational constraints. As a result, a job may cause blocking because it has to remain at a given station after an operation has been completed until space in front of the next station in its routing becomes available. Despite this practical reality, the Workload Control literature typically assumes infinite buffer limits and therefore neglects the impact of blocking. Using simulation, we highlight the direct, detrimental impact of blocking in both the pure and general flow shop. Workload Control order release dampens the effect of blocking and improves overall performance. This makes Workload Control order release even more important in the context of shops with blocking or physical space constraints. Further analysis reveals that the impact of blocking is less pronounced in the pure flow shop given its directed routing. Finally, most of the blocking that occurs is because jobs cannot enter the shop, i.e. there is no space in front of the gateway station. This re-emphasises the close relationship between blocking and release methods that limit the workload, and it highlights the importance of workload balancing.

Pengembangan Algoritma Hybrid Flowshop Three-Stage Dengan Mempertimbangkan Waktu Setup

Hybrid flow shop scheduling is one topic that is often reviewed by researchers at this time. Hybrid flow shop scheduling is the development of problems from pure flow shop. Flow shop problems have one machine at each stage. In this problem, each stage of operation has a machine that is arranged in parallel. This article aims to discuss the issue of hybrid flow shop scheduling at three stage to minimize makespan. Some previous studies discussed scheduling problems by considering setup time. However, such research is generally for the problem of pure flow shop. Therefore, a new algorithm is proposed to solve the problem. The proposed algorithm is developed from the Pour heuristic algorithm. Several experiments were conducted to determine the performance of the proposed algorithm. This study uses ten numerical experiments. This experiment uses the number of jobs varying from 5 jobs to 50 jobs. The results of numerical experiments show that the proposed algorithm has better performance compared to some other algorithms. The proposed method produces an effective solution if it is used to solve problems with a large number of jobs..

Integration of Order Review and Release and Output Control with Worker’s allocation in a pure flow shop

With the increase of competitiveness and customer customization requirements, companies’ capability to predict and shorten lead-time is becoming an order winner factor. This is particularly crucial for high variability mix and low volume make-to-order companies. Production Planning and Control aims at the alignment between capacity and demand in order to improve production system performance along with lead-time reduction. Workload control is a planning production and control concept developed for high-variety low-volume companies. It aims at controlling the workload in the system by mean of two mechanisms: the input control and the output control. The former regulates the release of new orders in the system, while the latter controls the production capacity. Most of the existing studies focused only on input control, while the output control has been quite overlooked. Moreover, the few studies that combine the two controls were interested in showing the effect on performances and did not consider a specific output control strategy: they operationalized capacity adjustments as decreases of the processing time. This paper is a preliminary step in filling this gap: input control in the form of order review and release and worker’s allocation, as capacity adjustments strategy, are integrated in a pure flow shop. Worker’s allocation is meant not to increase the overall capacity of the system but to shift idleness periods of workers. Order review and release and Output Control integration (ORROCI) model is presented, showing how the two control mechanisms can be integrated and tested, through simulation. It takes into account both load distribution and capacity available in the system and it transfers workers only when there are imbalances amongst stations load. Preliminary results show that order review and release and worker’s allocation can be successfully integrated, achieving superior performances. Further researches can be pursed testing different labor flexibility and efficiency levels, along with different where, when and who rule concerning worker’s allocation.

Improve Algoritma Hodgson Untuk Meminimasi Jumlah Job Terlambat Pada Penjadwalan Flow shop

Since Johnson published a paper in 1954, the problem of job scheduling has received the attention of hundreds of practitioners and researchers, as one of the most studied topics in Operation research. Several heuristic studies have discussed the problem of flow shop scheduling to minimize the completion time (makespan). In this paper, we consider the problem of pure flow shop scheduling to minimize the number of jobs of tardy. We have developed a Hudson algorithm for minimization solution the number jobs of tardy. Hodgson's improved Heuristic algorithm was tested and compared to the EDD priority rule. The Numerical experimental results show the new algorithm provides a better solution than priority EDD. The improving Hodgson algorithm gives a minimum number of tardy jobs.

Improve Algoritma Hodgson Untuk Meminimasi Jumlah Job Terlambat Pada Penjadwalan Flow shop

Since Johnson published a paper in 1954, the problem of job scheduling has received the attention of hundreds of practitioners and researchers, as one of the most studied topics in Operation research. Several heuristic studies have discussed the problem of flow shop scheduling to minimize the completion time (makespan). In this paper, we consider the problem of pure flow shop scheduling to minimize the number of jobs of tardy. We have developed a Hudson algorithm for minimization solution the number jobs of tardy. Hodgson's improved Heuristic algorithm was tested and compared to the EDD priority rule. The Numerical experimental results show the new algorithm provides a better solution than priority EDD. The improving Hodgson algorithm gives a minimum number of tardy jobs.

Analysing the impact of uncertainty reduction on WLC methods in MTO flow shops

ABSTRACTWith more and more demanding customers, make-to-order (MTO) companies are becoming more important. Workload control (WLC) is specifically developed for MTO companies. Most previous studies have proposed solutions assuming no mismatch between planned and actual production time. However, in real situations, inaccurate estimation of processing time is a daily routine. This study focuses on processing time estimation error and evaluates performance of two different WLC order review and release (ORR) methods through simulation of a pure flow shop. Simulation results demonstrate that balancing workload is more effective than limiting workload at different error levels. However, with decrease in errors, difference in performance between limiting and balancing methods becomes wider. Further investigation shows that improving processing time estimation heavily affects the order selection process in balancing method, which is the main reason for performance improvement. Finally, aspects of Industry 4.0 are discussed in context of ORR methods in MTO flow shops.

On the beat of the drum: improving the flow shop performance of the Drum–Buffer–Rope scheduling mechanism

One of the main elements of the theory of constraints is its Drum–Buffer–Rope (DBR) scheduling (or release) mechanism that controls the release of jobs to the system. Jobs are not released directly to the shop floor – they are withheld in a backlog and released in accordance with the output rate of the bottleneck (i.e. the drum). The sequence in which jobs are considered for release from the backlog is determined by the schedule of the drum, which also determines in which order jobs are processed or dispatched on the shop floor. In the DBR literature, the focus is on the urgency of jobs and the same procedure is used both for backlog sequencing and dispatching. In this study, we explore the potential of using different combinations of rules for sequencing and dispatching to improve DBR performance. Based on controlled simulation experiments in a pure and general flow shop we demonstrate that, although the original procedure works well in a pure flow shop, it becomes dysfunctional in a general flow shop where job routings vary. Performance can be significantly enhanced by switching from a focus on urgency to a focus on the shortest bottleneck processing time during periods of high load.

Deconstructing bottleneck shiftiness: the impact of bottleneck position on order release control in pure flow shops

Bottleneck shiftiness is an important managerial problem that negatively affects shop floor manageability. It has therefore received much research attention. Yet research has focused on how protective capacity can be used to influence bottleneck shiftiness rather than on assessing its operational impact. The latter is complex to evaluate since changing the degree of bottleneck shiftiness influences utilization, which makes the results of different experimental settings non-comparable. To overcome this problem, we take a different approach. Bottleneck shiftiness is decomposed by investigating its underlying phenomenon: the impact of the bottleneck position. Using simulation, we demonstrate that tighter control can be exercised, and better performance achieved, the further upstream the bottleneck is positioned. It is consequently important to be aware of the direction of the bottleneck shift. If the bottleneck shifts upstream, performance is likely to improve rather than deteriorate as is implicitly assumed in the literature.

A Heuristic Based On Makespan Lower Bounds in Flow Shops with Multiple Processors

Minimum makespan scheduling of Flow Shops with Multiple Processors (FSMPs), also known as the Hybrid Flow Shop (HFS), is classified as NP complete. Thus, the FSMP largely depends on strong heuristics to develop solutions to makespan scheduling instances. An FSMP consists of m stages wherein each stage has one or more processors through which n jobs are scheduled. This paper presents a heuristic based on the lower bound developed in a prior work in order to determine good makespan solutions in the FSMP environment. In the environment studied in this work, the multiple machines available at a particular processing stage are identical processors. In order to evaluate the proposed heuristic, its performance is compared to makespans obtained via the use of modified pure flow shop heuristics. Results show that the proposed heuristic is indeed a strong heuristic for the FSMP and it provides makespans that are better than those provided by some of the already existing pure flow shop heuristics that have been adapted for the FSMP environment.

An Entropy Measure of Flow Dominance for Predicting Operations Performance

The flow of jobs within a system is an important operating characteristic that influences system performance. While the majority of previous studies on manufacturing performance consider product flows only as an implicit parameter of the design, we introduce an explicit measure of flow dominance based on entropy and test its efficacy in predicting the performance of manufacturing systems. In computing entropy flow dominance ( EFD), we aggregate information embedded in the routings of all products within a system into a single measure. EFD is designed to indicate on a 0–1 scale the level of flow dominance, where 1 represents a pure flow shop and 0 represents a pure job shop. The result is a simple measure that provides managers a way to explain and predict complex phenomena. Our experimental results indicate that EFD is a statistically significant determinant of manufacturing system performance. Furthermore, the model including EFD as an independent variable accurately predicts manufacturing system performance as measured by job flow time, flow time standard deviation, and work in process. We note that the same results can also apply to service systems, such as the “back‐room” low‐contact type systems, that have similar characteristics as manufacturing systems.

Card-based delivery date promising in pure flow shops with order release control

Card-based systems are simple, effective means of controlling production. Yet most systems concentrate on controlling the shop floor. They neglect other planning tasks, like estimating short, feasible due dates during customer enquiry management. A card-based version of the workload control concept for job shops – COBACABANA (COntrol of BAlance by CArd-BAsed Navigation) – was proposed in the literature to overcome this shortcoming. COBACABANA uses cards for due date setting and order release, making it a potentially important solution for small shops with limited resources. But many such firms operate as flow shops rather than job shops. Research demonstrated that COBACABANA’s release mechanism must be adapted if applied to a pure flow shop, but its approach to due date setting has not been evaluated in such an environment. We show COBACABANA has the potential to improve pure flow shop performance, but its due date setting procedure should be adapted compared to job shops. In a flow shop, due date estimation can also be further simplified by considering the load awaiting release to the first (gateway) station only while maintaining most performance benefits. The results are important for all card-based systems that aim to stabilise work-in-process, including kanban and ConWIP (Constant Work-in-Process).

COBACABANA (Control of Balance by Card Based Navigation): An alternative to kanban in the pure flow shop?

Kanban systems are widely applied in practice as they represent a simple yet effective means of controlling production. But they suffer from a lack of load balancing capabilities, which hinders their application even to pure flow shops if there is variability. In response, this study focuses on COBACABANA (Control of Balance by Card Based Navigation), a card-based production control approach based on the Workload Control concept that was recently introduced in the literature. COBACABANA was developed for high-variety job shop contexts, but we argue it can also provide an important control alternative to kanban systems in pure flow shops. We first show that, in the pure flow shop, the control loop structure of COBACABANA resembles that of a kanban system when the flow of jobs is controlled. But a distinct difference is COBACABANA׳s unique focus on load balancing. Using simulation, we then demonstrate the potential of COBACABANA to improve performance in a pure flow shop with high demand and processing time variability. Results show that a fixed gateway station – inherent to a pure flow shop – presents a structural constraint that makes COBACABANA׳s original starvation avoidance mechanism, which injects work to a starving station, dysfunctional. An alternative is prioritizing jobs with short processing times at upstream stations to ensure quick replenishment takes place at downstream stations threatened by starvation. This has important implications not only for COBACABANA but for priority dispatching. Although card-based systems are typically combined with first-come-first-served dispatching, our results suggest this may be inappropriate in flow shops with processing time variability.

No-wait flexible flowshop with uniform parallel machines and sequence-dependent setup time: a hybrid meta-heuristic approach

According to the state of the art of no-wait scheduling problem, practitioners have mostly concentrated on pure no-wait flow shop scheduling problem. In the most real world production cases, flow shops operate with uniform parallel machines at each stage to eliminate or reduce the bottleneck stages with aim of enhancing the efficiency of production. This paper deals with a no-wait scheduling problem considering anticipatory sequence-dependent setup times on the flexible flow shop environment with uniform parallel machines. The objective is to find the sequence which minimizes maximum completion time of jobs (i.e. makespan). Since this problem is known to be NP-hard, we introduce a novel approach to tackle the problem. In the solution approach, firstly a heuristic formulation is used for objective function evaluation. Afterwards, principles of meta-heuristic algorithms namely invasive weed optimization, variable neighborhood search and simulated annealing algorithms are hybridized as solution method of the problem. In addition, a Taguchi method is employed for calibration of parameters and operators of the proposed hybrid meta-heuristic. Various computational experiments in two scales of small and large are established to illustrate the effectiveness and robustness of the proposed method. Finally, the experimental results revealed the superiority of the performance of the hybrid meta-heuristic in comparison with original ones singularly.

Mathematical model and parallel genetic algorithm for hybrid flexible flowshop lot streaming problem

Lot streaming is the technique of splitting a given job into sublots to allow the overlapping of successive operations in multi-stage manufacturing systems thereby reducing production makespan. Several research articles appeared in literature to solve this problem and most of these studies are limited to pure flowshop environments where there is only a single machine in each stage. On the other hand, because of the applicability of hybrid flowshops in different manufacturing settings, the scheduling of these types of shops is also extensively studied by several authors. However, the issue of lot streaming in hybrid flowshop environment is not well studied. In this paper, we aim to contribute in bridging the gap between the research efforts in flowshop lot streaming and hybrid flowshop scheduling. We propose a mathematical model and a genetic algorithm for the lot streaming problem of several jobs in multi-stage flowshops where at each stage there are unrelated parallel machines. The jobs may skip some of the stages, and therefore, the considered system is a complex generalized flowshop. The proposed genetic algorithm is executed on both sequential and parallel computing platforms. Numerical examples showed that the parallel implementation greatly improved the computational performance of the developed heuristic.

A comprehensive mathematical model for hybrid flexible flowshop lot streaming problem

Article history: Received 1 September 2010 Received in revised form 15 October 2010 Accepted 20 October 2010 Available online 21 October 2010 Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing systems so that operations of a given lot can be overlapped. This technique can reduce manufacturing makespan and is an effective tool for time-based manufacturing strategy. Several research articles appeared in literature to solve this problem and most of these studies are limited to pure flowshop environments where there is only a single machine in each stage. On the other hand, because of the applicability of hybrid flowshops in different manufacturing settings, the scheduling of these types of shops is also extensively studied by several authors. However, the issue of lot streaming in hybrid flowshop environment is not well studied. In this paper, we aim to initiate research in bridging the gap between the research efforts in flowshop lot streaming and hybrid flowshop scheduling. We present a comprehensive mathematical model for scheduling flexible hybrid flowshop with lot streaming. Numerical example demonstrated that lot streaming can result in larger makespan reduction in hybrid flowshop where there is a limited research than in pure flowshop where research is abundant. © 2011 Growing Science Ltd. All rights reserved.