Towards the derivation of an integrated process cost-modelling technique for complex manufacturing systems

Cost modelling is used to support business decisions, especially, when the objective is to remain competitive on price and be able to realise outputs at low cost. Many researchers and industrialists have proposed and experimented with different cost-modelling techniques with a view to influencing design and production decisions at an early stage of the development process. This has led to cost-modelling methods which have been broadly classified in this paper as qualitative and quantitative. The paper identifies current best practice cost-modelling techniques and their performance in complex and dynamic manufacturing environments. The review served as a platform to support the recommendation for an integrated cost-modelling methodology. The integrated methodology is based on the strengths of cost engineering, enterprise modelling, system dynamics and discrete event simulation modelling techniques. The method can help in the redesign and re-engineering of products and processes for better cost and value indications; support investment decision analysis; help determine appropriate business and manufacturing paradigms; influence ‘make, buy or outsourcing’ decisions and serve as a key process improvement tool.     

Finite element simulation of plasticity induced crack closure with different material constitutive models

The study presented in this paper analyses the mechanical effects of material constitutive modelling on the numerical prediction of plasticity induced crack closure. With this aim, an elastoplastic stress analysis of a MT specimen was conducted using an implicit three dimensional finite element program. Two materials were studied: an Aluminium Alloy and a High Strength Steel. Several constitutive models were used to describe their cyclic behaviour, ranging from pure isotropic hardening or pure kinematic hardening models to combined isotropic plus kinematic hardening models. Numerical results showed clear differences in plastic behaviour and crack closure predictions for the different types of mechanical models used to describe the mechanical behaviour of the materials. The mechanisms of opening stress stabilization, usually observed in numerical simulations, are explained in this work by analysing the evolution of plastic deformation along the crack flanks. The same type of plastic deformation stabilization behaviour was observed independently of the hardening model in use.     

Demand sensing in e-business

In this paper, we identify various models from the optimization and econometrics literature that can potentially help sense customer demand in the e-business era. While modelling reality is a difficult task, many of these models come close to modelling the customer's decision-making process. We provide a brief overview of these techniques, interspersing the discussion occasionally with a tutorial introduction of the underlying concepts.     

Designing the spatial experience

3D and often full-size modelling is common practice in product designing. However, these models are usually made for final evaluation purposes after the design has been developed on the drawing board. This paper describes the use of 3D full-size modelling as a technique to be used from the very start of the design process, in conjunction with a design approach which emphasises the user's experience of the product.     

Data-driven cardiovascular flow modelling: examples and opportunities

High-fidelity blood flow modelling is crucial for enhancing our understanding of cardiovascular disease. Despite significant advances in computational and experimental characterization of blood flow, the knowledge that we can acquire from such investigations remains limited by the presence of uncertainty in parameters, low resolution, and measurement noise. Additionally, extracting useful information from these datasets is challenging. Data-driven modelling techniques have the potential to overcome these challenges and transform cardiovascular flow modelling. Here, we review several data-driven modelling techniques, highlight the common ideas and principles that emerge across numerous such techniques, and provide illustrative examples of how they could be used in the context of cardiovascular fluid mechanics. In particular, we discuss principal component analysis (PCA), robust PCA, compressed sensing, the Kalman filter for data assimilation, low-rank data recovery, and several additional methods for reduced-order modelling of cardiovascular flows, including the dynamic mode decomposition and the sparse identification of nonlinear dynamics. All techniques are presented in the context of cardiovascular flows with simple examples. These data-driven modelling techniques have the potential to transform computational and experimental cardiovascular research, and we discuss challenges and opportunities in applying these techniques in the field, looking ultimately towards data-driven patient-specific blood flow modelling.     

A review on neutron-irradiation-induced hardening of metallic components

Neutron irradiation alters the mechanical properties of metallic parts, which are exposed to service temperatures below 40% of their homologous temperature. These working conditions affect most of the components of fission nuclear reactors, making these parts susceptible during service to hardening, loss of ductility, localised plastic deformation and plastic instability. Additionally, there has been a continuous historical increase in the efficiency and service life of nuclear reactors, leading to more severe irradiation exposure during service. In this sense, understanding the mechanisms for the formation and evolution of irradiation-induced defects and their interaction with gliding dislocations is vital for the estimation of the service life of these components and the development of new radiation-resistant materials via alloy and microstructural design. The present paper reviews the use of atomic-scale modelling to simulate the generation and evolution of irradiation-induced defects. Additionally, the interaction between these defects and the gliding dislocations is revised in accordance with the continuum theory and atomic-scale modelling. Finally, the limitations and challenges facing the atomic-scale modelling of radiation damage and defect/dislocation interaction are briefly discussed.     

Business process modelling with stochastic networks

Modelling and analysis of business processes is critical to identify current business processes and to understand the contributions of new processes to the system. The quality of the results obtained by modelling and analysis significantly influences the success of business process reengineering (BPR). Therefore, a constant development in techniques used in business process modelling (BPM) and business process analysis (BPA) is necessary. However, when these proposed techniques are analysed it becomes obvious that they repeat the same basic approach, although a few offer different visions. In BPM development studies, the use of time-activity scheduling is often considered secondary (even neglected). The reason for this is that process modelling may be considered as project management and remain under this label. Many organizations may use these techniques in managing their daily activities if the maturity level and the simplicity of project management techniques are considered. It also enables the modelling of stochastic situations, otherwise not possible to do by any BPM method. In this study an existing business process with network properties is analysed using project scheduling techniques. Thus, business processes are described as networks, modelled and timed by network properties and stochastically analysed using GERT, a project based process scheduling method. Finally the results obtained by GERT are examined using the PERT-path approach.     

The impact of applying product-modelling techniques in configurator projects

This paper aims to increase understanding of the impact of using product-modelling techniques to structure and formalise knowledge in configurator projects. Companies that provide customised products increasingly apply configurators in support of sales and design activities, reaping benefits that include shorter lead times, improved quality of specifications and products, and lower overall product costs. The design and implementation of configurators are a challenging task that calls for scientifically based modelling techniques to support the formal representation of configurator knowledge. Even though extant literature has shown the importance of formal modelling techniques, the impact of utilising these techniques remains relatively unknown. Therefore, this article studies three main areas: (1) the impact of using modelling techniques based on Unified Modelling Language (UML), in which the phenomenon model and information model are considered visually, (2) non-UML-based modelling techniques, in which only the phenomenon model is considered and (3) non-formal modelling techniques. This study analyses the impact to companies from increased availability of product knowledge and improved control of product variants. The methodology employed is an exploratory survey, followed by interviews with 18 manufacturing companies providing customised products. The results indicate that companies using UML-based modelling techniques tend to have improved documentation of their product knowledge and an improved ability to reduce the number of product variants. This paper contributes to an increased understanding of what companies can gain from using more formalised modelling techniques in configurator projects, and under what circumstances they should be used.     

A composite computational model of liver glucose homeostasis. I. Building the composite model

A computational model of the glucagon/insulin-driven liver glucohomeostasis function, focusing on the buffering of glucose into glycogen, has been developed. The model exemplifies an ‘engineering’ approach to modelling in systems biology, and was produced by linking together seven component models of separate aspects of the physiology. The component models use a variety of modelling paradigms and degrees of simplification. Model parameters were determined by an iterative hybrid of fitting to high-scale physiological data, and determination from small-scale in vitro experiments or molecular biological techniques. The component models were not originally designed for inclusion within such a composite model, but were integrated, with modification, using our published modelling software and computational frameworks. This approach facilitates the development of large and complex composite models, although, inevitably, some compromises must be made when composing the individual models. Composite models of this form have not previously been demonstrated.     

Computer modelling of molecular ionic materials

This review describes recent advances and results achieved in the computer modelling of molecular ionic materials. These materials offer particular challenges in modelling because both ionic and covalent interactions contribute to their interatomic forces, and both are therefore responsible for their properties. Ionic materials have been extensively studied, as have molecular solids, and in modelling molecular ionic materials some techniques from both of these are borrowed and used.     

Visualization support to better comprehend and improve decision tree classification modelling process: a survey and appraisal

Data mining (DM) can be defined as the non-trivial process of identifying valid, novel, potentially useful and ultimately understandable patterns in data. Modelling is the crucial step where DM algorithms are applied in order to extract data patterns. In order for domain experts, who play significant roles in DM process, to make the most efficient and effective use of DM tools, these tools must incorporate appropriate visualization to facilitate the process of modelling. Yet, unfortunately, study of how visualization should be designed, particularly what components should be included and how to present them, has been rather limited. This paper surveys the current state of art in application of visualization techniques to better comprehend and improve the decision trees modelling process in three modes: visualization of tree models, visualization of model evaluation and visual interactive tree construction. A number of issues that have been overlooked and areas that need to be improved are identified through reviewing a collection of related research and examining six current DM softwares in terms of their design of a few important features in each mode of the visualization support to decision trees classification modelling. Although this article focuses on decision trees classification modelling, guidelines derived from this study can be beneficial to other modelling techniques as well. At the end of the paper, a desirable design of visualization support to DM modelling is proposed with a conceptual model.     

Some exactly solvable models for the statistical evolution of internal variables during plastic deformation

A class of exactly solvable statistical models for the evolution of internal (microstructural) variables in the course of plastic deformation is discussed. The common feature of these models is that the microstructural evolution is described in terms of stochastic differential equations (Langevin equations) which by a non-linear transformation can be mapped onto a Wiener or Ornstein–Uhlenbeck process. Examples include the textural evolution of planar polycrystals, the evolution of dislocation density distribution in unidirectional plastic deformation, and the combined dynamics of mobile dislocations and dislocation obstacles leading to slip-channel formation.     

Integrating GD&T into dimensional variation models for multistage machining processes

Recently, the modelling of variation propagation in multistage machining processes has drawn significant attention. In most of the recently developed variation propagation models, the dimensional variation is determined through kinematic analysis of the relationships among error sources and dimensional quality of the product, represented by homogeneous transformations of the actual location of a product's features from their nominal locations. In design and manufacturing, however, the dimensional quality is often evaluated using Geometric Dimensioning and Tolerancing (GD&T) standards. The method developed in this paper translates the GD&T characteristic of the features into a homogeneous transformation representation that can be integrated in existing variation propagation models for machining processes. A mathematical representation using homogeneous transformation matrices is developed for position, orientation and form characteristics as defined in ANSI Y14.5; further, a numerical case study is conducted to validate the developed methods.     

Interpretive structural modelling of risk sources in a virtual organisation

Speedier network decision making together with shorter time to bring items to market together with lower network operating costs all result from enhanced knowledge sharing. In addition reuse of enterprise and network knowledge resulting from improved capture means that any risk of repeating earlier project work is limited, repetition of past mistakes is reduced. Decisions are made with greater awareness of any risks involved and therefore there is likely to be a reduction in costs arising from faulty decisions and failed collaborations. While there are many advantages attached to the use of virtual organisations (VOs) there are also challenges, including risks that have become apparent through undertaking a review of the literature. In total 13 sources of risk were found stemming from the network related risks in a VO, where the emphasis of the study was placed. This paper contains a thorough study that will identify these threats as well as gaining a sound understanding of them by examining them one by one as they have been identified by the literature and previous studies. Subsequently, their relative importance will be analysed through the use of interpretive structural modelling (ISM) using information gathered in a questionnaire.     

Multidisciplinary perspective on accident investigation

The increasing complexity of many computer-controlled application processes is placing increasing demands on the investigation of adverse events. At the same time, there is a growing realisation that accident investigators must consider a wider range of contributory and contextual factors that help to shape human behaviour in the causes of safety-related incidents. A range of techniques have been developed to address these issues. For example (as we show in this paper), task modelling techniques have been extended from human computer interaction and systems design to analyse the causes and consequences of operator ‘error’. Similarly, barrier analysis has been widely used to identify the way in which defences either protected or failed to protect a target system from potential hazards. Many barriers fail from common causes, including misconceptions that can be traced back to early stages in the development of a safety-critical system. For instance, unwarranted assumptions can be made about the impact of training on operator behaviour in emergency situations. Similarly, barrier analysis can also be used before a system has been designed to inform the system model and make it more tolerant to errors by incorporating human and technical barriers into the design. Task models often uncover deep-rooted problems, for instance, in workload allocation across many different aspects of an interactive control system. It can be difficult to use barrier and task analysis to trace these common causes that lie behind the failure of many different defences. In order to deal with this complex combination of contributory factors and systems, we promote the use of abstraction (via models) as a way of representing these components and their interrelations whether it is design, construction or investigation. We use, to formally model an abstraction of the system. Additionally, the system model (described using a dialect of high-level Petri-nets) allows to reason about the system and to check conformance with the other models (task model, safety case and barriers). This paper, therefore, shows how an analysis of safety case arguments can be used to support the application of barrier, task, error and system analysis during the investigation of a command and control failure. The intention, in this paper, is to show that if an accident involved the failure of multiple barriers, it is also possible to trace the common causes of those failures back to the assumptions and arguments that are embodied within a safety case. Many countries require that safety cases demonstrate a system is ‘acceptably safe’ before they grant regulatory approval. These documents and the associated analytical techniques, therefore, provide a rich source of information about why command and control failures occurred. We demonstrate our approach on a fatal mining accident case study.     

Actant model of an extraction plant

Facing a growing complexity of industrial plants, we recognise the need for qualitative modelling methods capturing functional and causal complexity in a human-centred way. The present paper presents actant modelling as a functional modelling method rooted in linguistics and semiotics. Actant modelling combines actant models from linguistics with multilevel flow modelling (MFM). Thus the semantics of MFM functions is developed further and given an interpretation in terms of actant functions. The present challenge is to provide coherence between seemingly different categories of knowledge. Yet the gap between functional and causal modelling methods can be bridged. Actant modelling provides an open and provisional, but in no way exhaustive or final answer as to how teleological concepts like goals and functions relate to causal concepts. As the main focus of the paper an actant model of an extraction plant is presented. It is shown how the actant model merges functional and causal knowledge in a natural way.     

Problem identification in maintenance modelling: a case study

This paper is concerned with a problem identification and problem focus process in maintenance modelling. It endeavours to describe the process of moving from vague problem understanding towards more specific problem formulation and problem focus in the pursuit of practical decision making. This process was conducted using several analytical tools that complemented each other such as regression analyses, snapshot modelling and delay time modelling. As in many case studies related to maintenance modelling, this study also makes use of the experience of experts. It can be seen from the paper that subjective data estimates can prove to be a useful input for modelling. The analysis shows how simple modelling of maintenance problems can provide useful insights and better understanding of the problem in hand.     

Neural and fuzzy model performance evaluation of a dynamic production system

Although mathematical modelling techniques are very well developed, some production processes are difficult to be modelled by these modelling techniques or their math-models are too complex to be used for real-time control due to uncertain, imprecise and vague parameters’ relations. Spray dryers are complex, dynamic and ill-defined production processes. Their product (powder) must have a controllable size distribution consisting of spherical shapes and free-flowing characteristic of particles, which is required for an ideal pressing operation to overcome the product sticking in the dies. The relations of production process' parameters are highly non-linear. In this study, these non-linear parameters were studied and three different soft-computing intelligent models were developed and used to predict uncertain parameter relations. The first is the fuzzy model of the production process; the others are the artificial neural network (ANN) architectures; the back-propagation multilayer perceptron (BPMLP) algorithm and the radial basis function network (RBF). To deal with uncertainty and vagueness of the production system, a method (methodology) based on a fuzzy hierarchical analytic process modelling approach and two ANN approaches was applied. The performance of the BPMLP algorithm was found most vigorous than the RBF and fuzzy modelling approach.     

A constraint‐based approach to the modelling and analysis of packaging machinery

To enable packaging machinery manufacturers to compete at an international level, it is necessary to introduce them to more advanced design methods and technologies. For years, the evolution of packaging machinery has relied heavily on trial‐and‐error methods. The demands for continual increases in the performance capabilities of the machines, escalating legislation, environmental directives and changes in the characteristics of the product require rapid development of existing machine designs and the creation of new machines. This paper discusses the needs of SME packaging machinery manufacturers and identifies their requirements for methods in support of the design and redesign of packaging machinery. The need to identify, capture and manipulate design knowledge is critical for SMEs, where all too often design records are incomplete. Furthermore, a systems modelling approach that provides for support over the conceptual, embodiment and detailed design phases is essential for the rapid and effective development of designs. In order to meet these requirements, a methodology is proposed which incorporates ‘constraint modelling’ techniques. The methodology provides for experimental investigation and computer‐based modelling, which together aid the designer in gaining a fundamental understanding of the design problem. This enables the identification and representation of design knowledge, the determination of the limitations of an existing design, the evaluation of alternative designs and redesign strategies, as well as the embodiment, refinement and optimization of design solutions. The theory of ‘constraint modelling’ is discussed and the various phases of the methodology described. The applications of the methodology to a new machine design and a redesign program are also detailed. Copyright © 2001 John Wiley & Sons, Ltd.