Flow Time Performance Research Articles

Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey

Machine scheduling problems associated with semiconductor manufacturing operations (SMOs) are one of the major research topics in the scheduling literature. Lots of papers have dealt with different variants of SMOs’ scheduling problems, which are generally difficult to tackle theoretically and computationally. In this paper, the single machine, parallel machines, flow shops, and job shops scheduling problems from SMOs have been reviewed, based on different processing constraints, e.g., batch processing, auxiliary resources, incompatible job families, and reentrant flow, etc., with the cycle time, flow time, and throughput-related performance measures. Given the vast and diverse nature of the current literature, it is urgently needed to make a systematic survey in order to identify the important research problems, research trends, and the progress of the related solution methods, as well as clarify future research perspectives. We hope the findings and observations could provide some insights to the researchers and practitioners in this domain.

Developing a fuzzy-set-based shortcut layout approach for a semiconductor inter-bay handling system

Designing optimal material flow into a semiconductor inter-bay handling’s layout boosts production efficiency, increases yield and throughput, and cuts work-in-process (WIP) as well as cycle time. Intelligent layout of production plants is vital for modern manufacturing, and particularly so for 450-mm wafer-size semiconductor plants. In light of the particular bay nature of a semiconductor plant’s inter-bay, its shortcut design that results on more efficient flow movement become challenging differed from those of a manufacturing system. Additionally, a semiconductor bay’s shortcut layout considerations must address not just how to group stockers, but also how to determine the type of shortcut points and sequence of shortcut locations. Prior to mass production, the assessment expressed by designers’ artificial language, linguistic variable, for the shortcut design phase remains ambiguous and subjective. The need for efficient ways to take designers’ linguistic variables into account in the layout decision increases. The present study suggests a method based on fuzzy set theory to design the shortcut location for a semiconductor inter-bay equipped with a multiple-zone overhead shuttle (OHS) handling system. Unlike traditional layout approaches which can only handle quantitative data with Boolean logic problems, fuzzy-set-based methods offer a way to incorporate the attitude of designers using linguistic variables to represent a problem in decision making when designing semiconductor bay’s shortcut layout. The paper also develops an intelligent hybrid heuristic algorithm incorporating with the goal of maximizing in-sequence movements and minimizing total flow distance to search a better shortcut layout design. An illustrative example from a wafer foundry company is used to demonstrate that the fuzzy-set-based layout design found by the proposed layout method outperforms by other approaches in the OHS travel time, throughput, and flow time performance. The method suggested here can assist semiconductor facility designers in qualitatively and quantitatively improving the material flow and increasing production efficiency by solving their semiconductor bay’s shortcut layout problems.

Effect of routing flexibility and sequencing rules on performance of stochastic flexible job shop manufacturing system with setup times: Simulation approach

Routing flexibility is a major contributor towards flexibility of a flexible job shop manufacturing system. This article focuses on a simulation-based experimental study on the effect of routing flexibility and sequencing rules on the performance of a stochastic flexible job shop manufacturing system with sequence-dependent setup times while considering dynamic arrival of job types. Six route flexibility levels and six sequencing rules are considered for detailed study. The performance of manufacturing system is evaluated in terms of flow time related and due date–related measures. Results reveal that routing flexibility and sequencing rules have significant impact on system performance, and the performance of a system can be increased by incorporating routing flexibility. Furthermore, the system performance starts deteriorating as the level of route flexibility is increased beyond a particular limit for a specified sequencing rule. The statistical analysis of the results indicates that when flexibility exists, earliest due date rule emerges as a best sequencing rule for maximum flow time, mean tardiness and maximum tardiness performance measures. Furthermore, smallest setup time rule is better than other sequencing rules for mean flow time and number of tardy jobs performance measures. Route flexibility level two provides best performance for all considered measures.

Holonic supply chain: A study from family-based manufacturing perspective

In the contemporary business environment, to adhere to the need of the customers, caused the shift from mass production to mass-customization. This necessitates the supply chain (SC) to be effective flexible. The purpose of this paper is to seek flexibility through adoption of family-based dispatching rules under the influence of inventory system implemented at downstream echelons of an industrial supply chain network. We compared the family-based dispatching rules in existing literature under the purview of inventory system and information sharing within a supply chain network. The dispatching rules are compared for Average Flow Time performance, which is averaged over the three product families. The performance is measured using extensive discrete event simulation process. Given the various inventory related operational factors at downstream echelons, the present paper highlights the importance of strategically adopting appropriate family-based dispatching rule at the manufacturing end. In the environment of mass customization, it becomes imperative to adopt the family-based dispatching rule from the system wide SC perspective. This warrants the application of intra as well as inter-echelon information coordination. The holonic paradigm emerges in this research stream, amidst the holistic approach and the vital systemic approach. The present research shows its novelty in triplet. Firstly, it provides leverage to manager to strategically adopting a dispatching rule from the inventory system perspective. Secondly, the findings provide direction for the attenuation of adverse impact accruing from demand amplification (bullwhip effect) in the form of inventory levels by appropriately adopting family-based dispatching rule. Thirdly, the information environment is conceptualized under the paradigm of Koestler’s holonic theory.

The impact of lot-sizing in multiple product environments with congestion

We present a production planning model for a multiple product single machine dynamic lot-sizing problem with congestion. Using queuing models, we develop a set of functions to capture the nonlinear relationship between the output, lot sizes and available work in process inventory levels of all products in the system. We then embed these functions in a nonlinear optimization model with continuous variables, and construct an approximate solution to the original problem by rounding the resulting fractional solution. Computational experiments show that our model with congestion provides significantly better flow time and inventory performance than a benchmark model that does not consider the effects of congestion. These advantages arise from the use of multiple smaller lots in a period instead of a single large lot as suggested by conventional fixed-charge models without congestion.

Hybrid Queueing Theory and Scheduling Models for Dynamic Environments with Sequence-Dependent Setup Times

Classically, scheduling research in artificial intelligence has concentrated on the combinatorial challenges arising in a large, static domain where the set of jobs, resource capacities, and other problem parameters are known with certainty and do not change. In contrast, queueing theory has focused primarily on the stochastic arrival and resource requirements of new jobs, de-emphasizing the combinatorics. We study a dynamic parallel scheduling problem with sequence-dependent setup times: arriving jobs must be assigned (online) to one of a set of resources. The jobs have different service times on different resources and there exist setup times that are required to elapse between jobs, depending on both the resource used and the job sequence. We investigate four models that hybridize a scheduling model with techniques from queueing theory to address the dynamic problem. We demonstrate that one of the hybrid models can significantly reduce observed mean flow time performance when compared to the pure scheduling and queueing theory methods. More specifically, at high system loads, our hybrid model achieves a 15% to 60% decrease in mean flow time compared to the pure methodologies. This paper illustrates the advantages of integrating techniques from queueing theory and scheduling to improve performance in dynamic problems with complex combinatorics.

Comparison of different types of variability when using lot splitting in a dynamic open job shop

Previousshop floor control research has shown that lot splitting can improve flow time performance and that disruptions to smooth and even material flow through the production process are detrimental. We use a simulation model to extend the literature by differentiating between four types of variability that might disrupt material flow and by analysing their effects on the magnitude of flow time improvement from lot splitting in dynamic open job shops with a range of utilisations, setup to processing time ratios, and job sizes. We believe that we are the first to show that those types of variability have vastly different effects on how much flow time improvement lot splitting can offer. The findings will help manufacturers identify processes that will benefit the most from lot splitting and aid researchers in developing better experimental designs.

An integrated modeling approach for shop-floor scheduling and control problem of flexible manufacturing systems

Increasing automation and complexity of today's production systems affect the constraints of real-world shop-floor control and scheduling problems. To deal with these constraints, either the existing modeling and analysis techniques were improved or new scheduling approaches were developed. This study attempts to propose an object-oriented approach for modeling and analysis of shop-floor scheduling problem of flexible manufacturing systems (FMSs) using high-level Petri Nets (PNs). The graphical nature and mathematical foundation has made PN-based methods appealing in real-time scheduling and control of FMSs. In the proposed approach, we firstly construct an object-modeling diagram of an FMS and develop a heuristic rule-base to solve the resource contention problem then formulate the dynamic behavior of the system by high-level PNs. The modeling methodology is illustrated by an FMS, and the proposed rule-based system is compared with several dispatching rules with respect to part flow time and tardiness-related performance measures.

Flow time analyses of a simulated flexible job shop by considering jockeying

It has been essential to include flexibility in manufacturing policy making since variability in demand and products are considerably increasing. However, it is important to know and to monitor the proper level and type of flexibility that is required to obtain full benefits from it. This paper analyses the effects of flexibility on flow time performance of a simulated job shop. For that purpose, several scenarios are developed under four flexibility levels with two different machine selection rule and three types of dispatching rules. Furthermore, effect of jockeying as a queuing policy on the flow time performance is also investigated through simulation modeling. Results indicated that full flexibility is a preferable state for most of the cases. However, in some cases, chain configurations perform similar results since it combines the benefits of pooling and specialization. In addition, it is observed that a queue control mechanism like jockeying is an effective way to improve performance even though it may increase complexity of controlling policy.

An improved genetic algorithm for integrated process planning and scheduling

Process planning and scheduling are two of the most important functions involved in manufacturing process and they are actually interrelated; integration of the two is essential to improve the flexibility of scheduling and achieve a global improvement for the performance of a manufacturing system. In order to facilitate the optimization of process planning and scheduling simultaneously, a mathematical model for the integrated process planning and scheduling (IPPS) is established, and an improved genetic algorithm (IGA) is proposed for the problem. For the performance improvement of the algorithm, new initial selection method for process plans, new genetic representations for the scheduling plan combined with process plans and genetic operator method are developed. To verify the feasibility and performance of the proposed approach, experimental studies are conducted and comparisons are made between this approach and others with the makespan and mean flow time performance measures. The results show that the proposed approach on IPPS has achieved significant improvement in minimizing makespan and obtained good results for the mean flow time performance measure with high efficiency.

Efficient meta heuristic algorithms to minimize mean flow time in no-wait two stage flow shops with parallel and identical machines

The no-wait two stage flexible manufacturing problem is an important problem in flow shops. This paper investigates the no-wait two stage flexible flow shop with a minimizing mean flow time performance measure. Six meta-heuristic algorithms are developed to solve the problem. In addition some numerical experiments are established to compare the efficiency of the proposed algorithms to each other. The results of the simulation study are illustrated to testify to the performance of the proposed algorithms. This is followed by proposing the most efficient algorithm and giving concluding remarks and potential areas for further research.

A multi-product lot size in make-to-order supply chain using discrete event simulation and response surface methodology

This paper develops a simulation optimisation approach for solving the Lot-Sizing Problem (LSP) in Make-to-Order (MTO) supply chain. For this purpose, a discrete event simulation model was firstly implemented as a tool in estimating Order Mean Flow Time (OMFT) performance. Secondly, a multiple-objective optimisation was achieved by applying Response Surface Methodology (RSM). A comprehensive case study is detailed which involves a multi-product, multi-stage, multi-location production planning with capacity-constrained and stochastic parameters such as lot arrivals order, transit time, set-up time, processing time, etc. The objective of the proposed approach is to determine the fixed optimal lot size for each manufacturing product type that will ensure OMFT target value for each finished product type. The study results illustrate that the LSP in MTO sector is viable and provide a prototype for further research on simulation optimisation approaches.

Cross-training workers in Dual Resource Constrained systems with heterogeneous processing times

In this paper, we explore the effect of cross-training workers in Dual Resource Constrained (DRC) systems with machines having different mean processing times. By means of queuing and simulation analysis, we show that the detrimental effects of pooling (cross-training) previously found in single resource constrained (SRC) heterogeneous systems are also apparent in DRC heterogeneous systems. Fully cross-training workers in DRC heterogeneous systems is only beneficial if the differences between mean processing times are not too large, otherwise cross-training should be pursued within homogeneous subgroups of machines. Due to the limited machine availability, DRC systems are unable to use some of the potential assignment flexibility from cross-trained workers (pooled queues) that can be used in SRC systems. However, it appears that this restriction in the DRC system may even improve the system mean flow (waiting) time performance compared to the SRC system for relatively large differences in processing time. Finally, in fully flexible multiple server queuing systems, restricting the assignment flexibility by applying a decentral when-rule (i.e. a commonly used labour assignment rule in practice and research) instead of a central when-rule also seems to improve the mean flow time performance under processing time differences.

Family-based dispatching: anticipating future jobs

Group Technology exploits similarities in product and process design to meet the diversity of customer demand in an economic way. In this paper we consider one of the implementations of this concept – family-based dispatching. Intrinsic to family-based dispatching is the grouping of similar types of products for joint processing. In this way the number of set-ups may be reduced. Consequently, lead-time performance of the shop can be improved. We extend existing rules for family-based dispatching by including data on upcoming job arrivals. Typically, this type of data resides in the minds of the operators, or is stored in a shop-floor control system. Its availability allows for (1) better estimates of the composition of a process batch for a family, (2) the consideration of families for which no products are available at the decision moment, and (3) the possibility to start set-ups in anticipation of future job arrivals. The potential of including forecast data in decision-making is demonstrated by an extensive simulation study of a single-machine shop. Results indicate the possibility of significant improvements of flow time performance.

Performance of Workstation With Offline and Integrated Metrology

One of the present developments in the semiconductor industry is integration of metrology tools in the main process tool, instead of measuring wafers stand-alone, i.e., at an offline metrology tool. One of the advantages expected from integrated metrology (IM) compared to offline metrology (OM) is an earlier detection of out-of-control situations in the process tool. Despite of the advantages expected from IM, manufacturers will only convert to IM if investments can be justified. The objective of this paper is to compare the effect of process failures in the processes on the performance of a workstation using OM or IM. Analytical relations for effective process time and flow time of a workstation, containing a single machine or a cascade machine, are derived and validated for both OM and IM. In the analysis, the performance of OM and IM practices are compared and the influence of process failures is investigated. It can be concluded that a workstation containing a single machine or a cascade machine with IM outperforms a workstation with OM with respect to flow time for lower levels of utilization. For higher levels of utilization the effective (maximal achievable) throughput of a workstation with IM is limited because of the increase of the process time by the quality measurement time. If the frequency of process failures is reduced by improving the workstation, a better performance of a workstation with OM is obtained with respect to flow time and throughput at higher utilization levels. In all situations, a workstation with OM and no transport time (inline metrology) has the best flow time performance. The opinion in industry that IM has a positive influence on flow time performance is not shared by the results of this paper. The results are obtained, e.g., by making no distinction between different metrology inspections or by neglecting the influence of a metrology module upon the reliability of the workstation. In practice, metrology configurations may not perform equally so that a preference for one of them might be based on other considerations than flow time performance

A fuzzy dispatching strategy for due-date scheduling of FMSs with information delays

Conventional dispatching strategies for FMSs with routing flexibility have typically employed simple heuristics such as work-in-next-queue (WINQ) and number-in-next-queue (NINQ). The effectiveness of these heuristics, however, deteriorates in FMSs whose operational environment must cope with information delays that are non-negligible in comparison to part processing times. Such delays could arise from planned activities, e.g., acquisition, selection, processing, and transfer of plant-wide system status information as well as from unplanned events such as ERP/IT system malfunctions, mismatch of software interfaces, and erroneous inventory master files, for example. Uncertainties from information delays make a strong case for the introduction of fuzzy controllers for making scheduling decisions. This paper introduces a novel fuzzy logic-based dispatching strategy to cope with a specific manifestation of information delays, called status review delay within FMSs. Status review information delays impact system performance adversely because of the obsolescent nature of the information used in the determination of dispatch decisions. A fuzzy dispatching strategy (FDS), designed specifically for deployment within FMSs where information delays are manifest, provides an appropriate alternative to conventional dispatching strategies such as WINQ and NINQ. In the design of an FDS, relevant system-based parameters are fuzzified and an appropriate rule base is designed. Simulation experiments demonstrate the superiority of an FDS over the conventional WINQ dispatching strategy using the mean tardiness, percent tardy, and mean flowtime performance measures.

Impact of operation flexibility and dispatching rules on the performance of a flexible manufacturing system

Operation flexibility is one of the eight common types of flexibility that exist in flexible manufacturing systems. Dispatching rules are commonly used in loading the machines. This paper studies the effects of different levels of operation flexibility and various dispatching rules on the performance of a flexible manufacturing system. The system performance considered is mean flow time. Simulation results indicate that the mean flow time cannot be always improved by increasing the level of operation flexibility. Altering the dispatching rules seems to have a more significant effect on the mean flow time performance than changing the level of operation flexibility.

Comparing variance reduction to managing system variance in a job shop

Variance within the manufacturing system leads to uneven shop loads, long manufacturing lead times, and unreliable customer service. This study compares techniques that reduce system variance to techniques that manage system variance. The study is placed in a dual resource constrained job shop. Results indicate that reducing system variance improves flow time and customer service performance measures, such as mean tardiness and percent tardy jobs more than techniques that react to system variance.

Shop Performance Implications of Using Cells, Partial Cells, and Remainder Cells*

ABSTRACTThis paper considers the application of cellular manufacturing (CM) to batch production by exploring the shop floor performance trade‐offs associated with shops employing different levels of CM. The literature has alluded to a continuum that exists between the purely departmentalized job shop and the completely cellular shop. However, the vast majority of CM research exists at the extremes of this continuum. Here, we intend to probe performance relationships by comparing shops that exist at different stages of CM adoption. Specifically, we begin with a hypothetical departmentalized shop found in the CM literature, and in a stepwise fashion, form independent cells. At each stage, flow time and tardiness performance is recorded. Modeling results indicate that, depending on shop conditions and managerial objectives, superior shop performance may be recorded by the job shop, the cell shop, or by one of the shops between these extreme points. In fact, under certain conditions, shops that contain partially formed cells perform better than shops that use completely formed cells. Additional results demonstrate that in order to achieve excellent performance, managers investigating specific layouts need to pay especially close attention to changes in machine utilization as machine groups are partitioned into cells.

Scheduling unbalanced cellular manufacturing systems with lot splitting

Recently, a large number of studies have addressed lot splitting as a means to reduce flow times as well as improve due date performance. Furthermore, a number of studies have examined scheduling policies in cellular manufacturing systems. These studies have been conducted under a variety of experimental factors, shop structures and operational assumptions. This study examines scheduling cellular manufacturing systems in the presence of lot splitting. In addition, we utilize various scheduling policies to test formally the underlying principles of the synchronous manufacturing philosophy. This is accomplished by utilizing exhaustive and non-exhaustive scheduling heuristics simultaneously at bottleneck and non-bottleneck workcentres. The results indicate that, under certain conditions, performing additional set-ups before the bottleneck can improve due date performance without an adverse effect on average flow time. Furthermore, we show that incurring additional set-ups after the bottleneck does not improve due date performance and may deteriorate flow time performance. These results conflict with some of the tenets of the synchronous manufacturing philosophy.