Evaluations of operational control rules in scheduling a flexible manufacturing system

In this paper, computer simulation is used to evaluate the effects of various control rules on the performance of a flexible manufacturing system (FMS) operating under different manufacturing environment. Alternative routings are available, if the operation of a part can be performed by more than one machine. Three control rules, namely, dynamic alternative routings, planned alternative routings, and no alternative routings, are proposed to control the selection of alternative routings for each part. The effects of the universal loading station and also those of the dedicated loading station are investigated. In addition, the impact of buffer existence on the system’s performance is also examined by considering machines with and without local buffers. The effects of changing production ratios of different part types on the performance of various operational control rules are also investigated. Moreover, the effects of system having machine breakdown are also discussed. The simulation results indicate that the FMS with dedicated loading stations outperforms the FMS with universal loading stations in all aspects. The dynamic alternative routings generally produces the best results in system performance if the universal loading station is provided. The planned alternative routings generally gives the best system performance when both the dedicated loading stations and local buffers are available. The no alternative routings usually remains at the bottom of the rank, occasionally with some exceptions. Problems in actual implementation are also highlighted.     

A parametric fuzzy logic approach to dynamic part routing under full routing flexibility

Manufacturing flexibility is a competitive weapon for surviving today’s highly variable and volatile markets. It is critical therefore, to select the appropriate type of flexibility for a given manufacturing system, and to design effective strategies for using this flexibility in a way to improve the system performance. This study focuses on full routing flexibility which includes not only alternative machines for operations but also alternative sequences of operations for producing the same work piece. Upon completion of an operation, an on-line dispatching decision called part routing is required to choose one of the alternatives as the next step. This study introduces three new approaches, including a fuzzy logic approach, for dynamic part routing. The fuzzy part routing system adapts itself to the characteristics of a given flexible manufacturing system (FMS) installation by setting the key parameters of the membership functions as well as its Takagi-Sugeno type rule base, in such a way to capture the bottlenecks in the environment. Thus, the model does not require a search or training for the parameter set. The proposed approaches are tested against several crisp and fuzzy routing algorithms taken from the literature, by means of extensive simulation experiments in hypothetical FMS environments under variable system configurations. The results show that the proposed fuzzy approach remains robust across different system configurations and flexibility levels, and performs favourably compared to the other algorithms. The results also reveal important characteristic behaviour regarding routing flexibility.     

Distributed bottleneck control for repetitive production systems

A bottleneck control problem for general periodic job shops with blocking where each machine has an input buffer of finite capacity is investigated. The job shop considered consists of a set of workflows competing with each other for access to common machines. A distributed buffer control policy that restricts a job entering an input buffer of a local machine in a specific sequence is proposed. The conditions sufficient for design and allocation of dispatching rules are presented. The system time and the rate of machine utilization are considered as the evaluation criteria. Finally, the procedure aimed at scheduling periodic job shops is provided.     

The effect of responsiveness of the control-decision system to the performance of FMS

In Flexible Manufacturing System (FMS), decision-making process is one of the key aspects for its performance enhancement, particularly for shop-floor control, where operation managers need to make a large number of control decisions. A term called ‘response-time’ in decision-making process has been defined in this study, which refers to a lead time in decision-making and its implementation. This paper contributes a methodology for decision-maker to study the decision-making process and identify a suitable decision-making approach, while considering critical factors such as decision automation levels, routing flexibility levels, and control strategies. Considering the complexity in modelling an FMS with routing flexibility levels, control strategies (sequencing and dispatching rules), and decision-making process with information system, computer simulation modelling has been employed to study the makespan performance. The results show that decision-making process with response-time for FMS control performs as good as with the real-time control when routing flexibility level is low. Furthermore, under some specific situations, it even outperforms the real-time control. This research gives insight to decision-maker to identify whether a decision system with response-time will be more suitable and economically justified, or real-time decision-making system is more appropriate.     

Dynamic routing strategies for JIT production in hybrid flow shops

In production processes, just-in-time (JIT) completion of jobs helps reduce both the inventory and late delivery of finished products. Previous research which aims to achieve JIT job completion mainly worked on static scheduling problems, in which all jobs are available from time zero or the available time of each job is known beforehand. In contrast, dynamic scheduling problems which involve continual arrival of new jobs are not much researched and dispatching rules remain the most frequently used method for such problems. However, dispatching rules are not high-performing for the JIT objective. This study proposes several routing strategies which can help dispatching rules realize JIT completion for jobs arriving dynamically in hybrid flow shops. The routing strategies are based on distributed computing which makes realtime forecast of completion times of unfinished jobs. The advantages include short computing time, quick response and robustness against disturbance. Computer simulations show that the performance of dispatching rules combined with the proposed routing strategies is significantly higher than that of dispatching rules only and that of dispatching rules combined with the previous routing methods.     

Using a CATS database for alternative machine loading

Industry is currently utilizing the computer to generate shop time standards. A logical extension of these systems is to include the ability to generate alternative standards, which then permits alternative machine routings. The purpose of this paper is to discuss the advantages of using alternative machine routings to improve the productivity of the machine shop. Through an example problem, it is shown that total production requirements are completed sooner by using alternative machines, and overall machine utilization is improved.     

Outsourcing strategy in two-stage call centers

This paper considers ‘two-stage’ call centers where some incoming calls are completed by first service while others require an additional second service. Although this type of call center is not uncommon, it has not been dealt with, if any, in the call center literature. In this paper, we introduce the concept of the ‘two-stage’ call center and discuss its features. Furthermore, we develop an effective outsourcing strategy in ‘two-stage’ call centers. To this end, we model ‘two-stage’ service system and propose several call routing structures. The structures are compared through numerical test and conventional queueing theories form the theoretical basis of our study.     

Routing distributions and their impact on dispatch rules

Motivated by the job-shop production process of our industry partner, we examine dispatching rules effects on two key performance indicators (KPIs) – job lateness and the percentage of late jobs. In the literature, authors use the uniform distribution to generate random job shop data. In addition to our discussion on dispatching rules, we propose an alternative idea for random job shop data, the routing distribution, and we compare dispatching rules performance using KPI frontiers under different routing distributions. We show that using their current dispatch rule, earliest operation due date (EODD), the industry partner is never worse off, even as their job-shop’s operational environment changes. We further show that using multiple dispatch rules across several job-shop departments does improve a job-shop’s performance on the KPIs, though the improvement is small and in some cases may not be statistically significant. In addition, we find that EODD is one of several dispatching rule which consistently lie on the KPI frontier for different job routing distributions. We find that dispatching rule performance is greatly affected by the routing distribution of the job-shop where the rules are employed. Lastly, we leave the readers with some insight into determining which dispatch rules and routing distributions should be considered for different job shops.     

Interpreting SWRL Rules in RDF Graphs

An unresolved issue in SWRL (the Semantic Web Rule Language) is whether the intended semantics of its RDF representation can be described as an extension of the W3C RDF semantics. In this paper we propose to make the model-theoretic semantics of SWRL compatible with RDF by interpreting SWRL rules in RDF graphs. For dealing with SWRL/RDF rules, we regard ‘Implies’ as an OWL class, and extract all ‘Implies’ rules from an RDF database that represents a SWRL knowledge base. Each ‘Implies’ rule is grounded through mappings built into the semantic conditions of the model theory. Based on the fixpoint semantics, a bottom-up strategy is employed to compute the least Herbrand models.     

Using simulation and multi-criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors

Dispatching rules are important to the performance of a manufacturing system. Selective applications of different priority rules at different processing stages in a multiple workstation manufacturing system have a positive impact on shop performance. This type of problem is a combinatorial dispatching decision. However, no dispatching rule can consistently produce better performance than all other rules under a variety of operating conditions and criteria. It is the purpose of this study to provide a robust solution for a dispatching decision that will have ‘good’ performance under different operating scenarios. In this paper a simulation case of a flow shop with multiple processors is proposed, specifically a multi-layer ceramic capacitor manufacturing system. Two multiple criteria decision-making methods – techniques for order preference by similarity to ideal solution (TOPSIS) and an analytic hierarchy process (AHP) – in combination with Taguchi orthogonal array are used to find the most suitable dispatching rule for every workstation. The results show that for 15 production scenarios and 4 criteria this combinatorial dispatching rule is robust, in the sense that it outperforms other commonly employed strategies.     

A multiple-objective grouping genetic algorithm for the cell formation problem with alternative routings

This paper addresses the cell formation problem with alternative part routings, considering machine capacity constraints. Given processes, machine capacities and quantities of parts to produce, the problem consists in defining the preferential routing for each part optimising the grouping of machines into manufacturing cells. The main objective is to minimise the inter-cellular traffic, while respecting machine capacity constraints. To solve this problem, the authors propose an integrated approach based on a multiple-objective grouping genetic algorithm for the preferential routing selection of each part (by solving an associated resource planning problem) and an integrated heuristic for the cell formation problem.     

Modelling for flexible manufacturing systems and structural properties of optimal work routing policy

We consider flexible manufacturing systems (FMSs) which are composed of a set of workstations linked together with a material handling system (MHS). Each workstation consists of an input buffer, a single machine and an output buffer. The MHS consisting of a single cart routes work among the workstations according to the process paths required by the work. We deal with an optimal control problem in this FMS. We model the FMS as a closed queueing network. In the model, the cart routes the work to the workstations in accordance with a Markov routing with exponentially distributed routing time, and the machines process work with exponentially distributed processing time. An objective is to find a work routing policy that maximizes the total expected reward earned by operating machines. This optimal control problem is formulated as an undiscounted semi-Markov decision process. Structural properties of an optimal policy are analysed. Moreover, a sufficient condition is derived for the optimal policy to be of control limit type. An example is given to illustrate the result.     

Evaluation of a hierarchical reinforcement learning spoken dialogue system

We describe an evaluation of spoken dialogue strategies designed using hierarchical reinforcement learning agents. The dialogue strategies were learnt in a simulated environment and tested in a laboratory setting with 32 users. These dialogues were used to evaluate three types of machine dialogue behaviour: hand-coded, fully-learnt and semi-learnt. These experiments also served to evaluate the realism of simulated dialogues using two proposed metrics contrasted with ‘Precision-Recall’. The learnt dialogue behaviours used the Semi-Markov Decision Process (SMDP) model, and we report the first evaluation of this model in a realistic conversational environment. Experimental results in the travel planning domain provide evidence to support the following claims: (a) hierarchical semi-learnt dialogue agents are a better alternative (with higher overall performance) than deterministic or fully-learnt behaviour; (b) spoken dialogue strategies learnt with highly coherent user behaviour and conservative recognition error rates (keyword error rate of 20%) can outperform a reasonable hand-coded strategy; and (c) hierarchical reinforcement learning dialogue agents are feasible and promising for the (semi) automatic design of optimized dialogue behaviours in larger-scale systems.     

基于合同网协议交互投标的动态调度方法研究

柔性制造系统使生产加工路径有很多可选性，所以调度系统必须考虑机器调度问题。分配规则调度是一种最基本、最具影响力的动态调度方法。然而，分配规则调度方法很少考虑机器顺序选择。兼顾工件选择和机器选择两方面，本文运用交互投标过程，构建基于合同网协议调度的协商规则。研究作业车间动态调度问题，提出并构建了5种合同网规则调度方法。通过实验分析结果表明，基于合同网交互投标模式的规则调度能够大大改善调度系统性能，提高设备的利用率和设备负荷平衡指标。     

The role of student learning styles, gender, attitudes and perceptions on information and communication technology assisted learning

The present study adopts an illuminative approach to evaluate students’ initial attitudes towards the use of information and communication technology (ICT). Ninety-nine undergraduate science students participated in this study and their learning styles were classified according to Honey and Mumford (1986) (Honey, P., Mumford, A., 1986. The Manual of Learning styles. Peter Honey, 10 Linden Avenue, Maidenhead) learning style questionnaire. Student learning styles were classified as activist, reflector, theorist, or pragmatist. No significant difference in learning styles was observed between genders and between student cohorts. Six dimensions to student attitudes toward ICT were identified as follows; ‘comfort’, ‘interactivity’, ‘self-satisfaction’, ‘value new technology’, ‘experience’ and ‘context’. Students exhibited low scores in the attitude dimensions of ‘value new technology’, ‘interactivity’ and ‘context’ indicating that they were uncomfortable with computers, were unhappy about the lack of personal contact and would prefer to learn in a more traditional mode. A significant, though weak, negative correlation between the ‘theorist’ and the ‘interactivity’ and ‘context’ attitude dimensions was also observed. In addition, based on the results of this study it appears that first year students exhibit a more positive perception of ICT supported learning than second and third year students. Though the use of ICT in higher education is becoming more widespread based on the results of this study student use of the technology may be limited by a negative attitude toward a style of teaching which is not consistent with their past learning experiences.     

Automated system for machine tool capacity and utilization

An automated system based on Symphony spreadsheet software has been developed to monitor machine tool utilization and capacity in a small- to medium-sized machine shop. This application compiles reports on annual machine tool requirements and use from production routing data for a shop producing over 100 different small machined parts with batch sizes ranging from 100 to 1000 parts and up to 25,000 parts per year. The operational routings for approximately 30 parts are currently stored in the system. Levels of utilization are analyzed, which aids in determining the need for addition equipment or multiple workshifts, and thereby helps balance the workload and product flow. Valuable information was compiled in a special report for layout of a new shop facility. Group technology cell arrangements of equipment were analyzed for capacity and utilization. Many Symphony spreadsheet and data base management features were used to produce this program. The final system incorporated menu systems for users unfamiliar with this spreadsheet software.     

The influence of self-esteem and locus of control on perceived email-related stress

Electronic mail has become an indispensable tool in business and academia, and personal use is increasing every day. However, there is also evidence that Email, unlike more traditional communication media, can exert a powerful hold over its users and that many computer users experience stress as a direct result of email-related pressure. This paper develops a three-fold typology of orientations to email: ‘relaxed’, ‘driven’ and ‘stressed’. It further investigates whether the personality traits of self-esteem and locus of control are associated with email-related stress. It finds that low self-esteem is associated with the ‘driven’ orientation. It further suggests that the ‘stressed’ orientation may be related to how distractive email is perceived to be, compared with other forms of communication.     

Efference copies in neural control of dynamic biped walking

In the early 1950s, von Holst and Mittelstaedt proposed that motor commands copied within the central nervous system (efference copy) help to distinguish ‘reafference’ activity (afference activity due to self-generated motion) from ‘exafference’ activity (afference activity due to external stimulus). In addition, an efference copy can be also used to compare it with the actual sensory feedback in order to suppress self-generated sensations. Based on these biological findings, we conduct here two experimental studies on our biped “RunBot” where such principles together with neural forward models are applied to RunBot’s dynamic locomotion control. The main purpose of this article is to present the modular design of RunBot’s control architecture and discuss how the inherent dynamic properties of the different modules lead to the required signal processing. We believe that the experimental studies pursued here will sharpen our understanding of how the efference copies influence dynamic locomotion control to the benefit of modern neural control strategies in robots.     

An ethnographic, action-based approach to human experience in virtual environments

This paper addresses a sensitive issue, of presence experienced by people interacting with a virtual environment (VE). Understanding ‘presence’, both theoretically and empirically, is important for designers interested in building effective computer-mediated environments for learning and work activities. The concept of presence has been treated mostly as a state of mind, to be investigated through ‘objective’ and ‘subjective’ measurement devices. The authors propose to add a different approach, which can address presence as an action-based process. This approach considers presence as the ongoing result of the actions performed in an environment and the local and cultural resources deployed by actors. In this sense, ‘presence’ can be captured by monitoring the sequence of participants’ actions and the aspects of the environment that are involved in this process; discourse/interaction analysis represents a fitting method for this goal. Sequences of interaction with a virtual library are used to illustrate some core aspects of an ethnographic, action-based approach to presence, such as the action possibilities envisaged by participants, the configuration of the virtual objects, the norms that regulate the interaction, the resources that are imported in the VE. These aspects are a necessary step to understand users’ presence in the VE and to plan consequent interventions to ameliorate the design of the interface.     

Learning by local kernel polarization

The problem of evaluating the quality of a kernel function for a classification task is considered. Drawn from physics, kernel polarization was introduced as an effective measure for selecting kernel parameters, which was previously done mostly by exhaustive search. However, it only takes between-class separability into account but neglects the preservation of within-class local structure. The ‘globality’ of the kernel polarization may leave less degree of freedom for increasing separability. In this paper, we propose a new quality measure called local kernel polarization, which is a localized variant of kernel polarization. Local kernel polarization can preserve the local structure of the data of the same class so the data can be embedded more appropriately. This quality measure is demonstrated with some UCI machine learning benchmark examples.