Representing function-technology platform based on the unified modelling language

Product platforms are used in many industries to allow a variety of products to be offered to the market while levering commonality in components. The reported approaches to designing product platforms assume mature and stable design and manufacturing technologies. Consequently, product platforms are not applicable in the semiconductor equipment manufacturing industries, where the technologies keep evolving and cannot be frozen in the product development process. In response to the application limitations of traditional platforms, a concept of function-technology (FT) platform is put forward to assist semiconductor equipment manufacturers to efficiently design product families by reusing, in a structured way, functions and technologies. To shed light on the diverse constituent elements and the complex relationships inherent in an FT platform, this study focuses on its structural representation. A formalism of FT platform representation is developed based on the unified modelling language (UML). It consists of a generic functional structure, a generic technology structure and the mapping relationships in-between. An application case in a well-known semiconductor equipment manufacturer is also reported to present the structure of an FT platform and its representation based on the UML.     

Using Scrum and unified modelling language to analyze and design an automatic course scheduling system

This research used a case study methodology to examine large-scale software projects accomplished despite ambiguous customer requirements. This study adopted Scrum as the agile software development method and used unified modelling language (UML) diagrams to enhance design implementation documents and improve the software development process. This study presented how the case company explored a Scrum-based automatic course scheduling system for elementary and secondary schools. Through interviews, the case company incorporated customers’ requirements by using the corresponding UML diagrams, which helped the project team document the software development process and design the functions to satisfy customer demand. Then, the proposed method was introduced to the automatic elementary and secondary school course scheduling system project undertaken by the case company, verifying the feasibility of the proposed method. A few problems arose in the proposed software development process, and remedies were discussed. Software companies could use these results as a reference when implementing a large-scale software project with ambiguous customer requirements.     

Supply chain modelling and managing,using timed coloured Petri nets: a case study

This paper aims at developing a new methodology for designing and managing a supply chain (SC) and, at the same time, for evaluating the performance of every stakeholder involved in a production chain. The methodology proposed has been applied to a footwear supply chain and is based on coloured Petri nets (CPNs). The supply chain analysed in this paper is a complex production system consisting of a network of manufacturers and service suppliers related to logistics systems that provide transportation and storage. The model developed uses coloured, timed Petri nets to represent a supply chain and it is such that resources are the Petri Net (PN) places, the tokens are jobs, orders and/or products, while the colours represent job attributes. These colours are used to encode different data types and values that are attached to tokens. A “coloured token” represents a specific production order or a certain amount of a particular material supplied. Thus, it can be processed in different ways and it can be easily localised within the CPN model. The use of coloured Petri nets allows companies to create a compact representation of states, actions and events of the modelled system. The particular structure of this network allows the designers the easy realisation of a simulator using an “object-oriented”, dedicated programming, which is a useful tool for developing what-if analyses.     

Modelling the lymphatic system: challenges and opportunities

The lymphatic system is a vital part of the circulatory and immune systems, and plays an important role in homeostasis by controlling extracellular fluid volume and in combating infection. Nevertheless, there is a notable disparity in terms of research effort expended in relation to the treatment of lymphatic diseases in contrast to the cardiovascular system. While similarities to the cardiovascular system exist, there are considerable differences in their anatomy and physiology. This review outlines some of the challenges and opportunities for those engaged in modelling biological systems. The study of the lymphatic system is still in its infancy, the vast majority of the models presented in the literature to date having been developed since 2003. The number of distinct models and their variants are few in number, and only one effort has been made thus far to study the entire lymphatic network; elements of the lymphatic system such as the nodes, which act as pumps and reservoirs, have not been addressed by mathematical models. Clearly, more work will be necessary in combination with experimental verification in order to progress and update the knowledge on the function of the lymphatic system. As our knowledge and understanding of its function increase, new and more effective treatments of lymphatic diseases are bound to emerge.     

Dynamical modelling of haematopoiesis: an integrated view over the system in homeostasis and under perturbation

A very high number of different types of blood cells must be generated daily through a process called haematopoiesis in order to meet the physiological requirements of the organism. All blood cells originate from a population of relatively few haematopoietic stem cells residing in the bone marrow, which give rise to specific progenitors through different lineages. Steady-state dynamics are governed by cell division and commitment rates as well as by population sizes, while feedback components guarantee the restoration of steady-state conditions. In this study, all parameters governing these processes were estimated in a computational model to describe the haematopoietic hierarchy in adult mice. The model consisted of ordinary differential equations and included negative feedback regulation. A combination of literature data, a novel divide et impera approach for steady-state calculations and stochastic optimization allowed one to reduce possible configurations of the system. The model was able to recapitulate the fundamental steady-state features of haematopoiesis and simulate the re-establishment of steady-state conditions after haemorrhage and bone marrow transplantation. This computational approach to the haematopoietic system is novel and provides insight into the dynamics and the nature of possible solutions, with potential applications in both fundamental and clinical research.     

A fractal perspective-based methodological framework for supply chain modelling and distributed simulation with multi-agent system

With the development of global economy, supply chain, as a recognised complex system, is becoming more complex for analysis. In this context, it is worth introducing the perspective of complex system in perceiving and modelling of supply chain system to address its dynamic, stochastic and uncertain characteristics. Therefore, this paper proposes a methodological framework of supply chain modelling and simulation based on the fractal perspective, and presents an all-round and systematic exposition of concept modelling and distributed simulation by means of multi-agent technology. In this framework, different supply chain scenarios focusing on manufacturing, inventory and transportation can be easily modelled and simulated at different scales and levels. In addition, a prototype system which implements the methodological framework and the key implementation techniques are presented as well. Finally, a supply chain example, which supposes manufacturer as the core member, is modelled and simulated with the prototype system to illustrate the effectiveness of the proposed framework.     

带闭链机器人动力学建模的符号－数值技术

对带闭链的（并联型）机器人的动力学建模采用了符号－数值方法，在计算机上获得了一、二阶影响系数矩阵和动力学方程中各矩阵元素的最简解析表达式，解决了当分支的广义坐标数不等于６时出现的长方形（奇异）矩阵求逆的解析表达问题。此外，还将键图法与符号－数值技术结合用于机器人动力学的建模及仿真。     

A decision support framework for global supply chain modelling: an assessment of the impact of demand,supply and lead-time uncertainties on performance

We developed a decision support framework for a global manufacturer of specialty chemicals to study the relative impact of demand, supply and lead-time uncertainties on cost and customer service performance. Our approach combines optimisation and simulation methodologies as follows: mathematical models provide optimal plans via a novel approach to the supply chain planning mechanism of the Company. Simulation models execute the supply chain plans so as to allow the examination of the outcomes under the various sources of uncertainty. The iterative use of optimisation and simulation methodologies allows the user the benefit of obtaining optimal solutions while revealing the impact of uncertainties on system performance. Our results indicate that demand uncertainty has the greatest negative impact on performance for the supply chain that we modelled in this study, emphasising the importance of effective forecasting. The relative importance of supply and lead-time uncertainties varies according to the performance measures. While our results are valid for the specific supply chain and the operating environment we modelled, our study emphasises the importance of the ability to model supply chains realistically to obtain valid and useful results.     

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population''s infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease''s specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (R_e) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age–class structure, and a maximum likelihood methodology allows us to estimate the model''s next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of ‘who-infected-who’. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias.     

Multi-scale computational modelling of the mechanical behaviour of the chitosan biological polymer embedded with graphene and carbon nanotube

A multi-scale modelling approach is employed to investigate the elasto-plastic behaviour of the pure chitosan biological polymer, as well as its composite when it is embedded with a graphene sheet, and a carbon nanotube. The model directly incorporates inter-atomic potentials, describing the energetics of molecular clusters, into a continuum-based computation without any need for a parameter fitting. The coupling of the atomistic and continuum levels is achieved via the adoption of the Cauchy-Born rule which provides a suitable framework for investigating the mechanical behaviour of materials undergoing large deformations. All data on atomic bonding, bond angle, bond torsion, and nonbonding interactions relevant to the molecular clusters are incorporated into the constitutive continuum model. The continuum point within a finite element (FE) mesh is represented by an atomic cluster, referred to as a nanoscopic representative volume element (NRVE). We have introduced a parameter R that represents the ratio of the volume of finite element within which the NRVE is embedded to the volume of the NRVE. It is shown that the variation of R directly affects the results on the stress-strain behaviour of the composite, and that for R ∼ 1.0, our computed results on the elastic modulus of the simple and composite systems are fair in agreement with the experimental data.     

Unravelling novel synergies between organometallic and biological partners: a quantum mechanics/molecular mechanics study of an artificial metalloenzyme

In recent years, the design of artificial metalloenzymes obtained by the insertion of homogeneous catalysts into biological macromolecules has become a major field of research. These hybrids, and the corresponding X-ray structures of several of them, are offering opportunities to better understand the synergy between organometallic and biological subsystems. In this work, we investigate the resting state and activation process of a hybrid inspired by an oxidative haemoenzyme but presenting an unexpected reactivity and structural features. An extensive series of quantum mechanics/molecular mechanics calculations show that the resting state and the activation processes of the novel enzyme differ from naturally occurring haemoenzymes in terms of the electronic state of the metal, participation of the first coordination sphere of the metal and the dynamic process. This study presents novel insights into the sensitivity of the association between organometallic and biological partners and illustrates the molecular challenge that represents the design of efficient enzymes based on this strategy.     

Finite element crash simulations of the human body: Passive and active muscle modelling

Conventional dummy based testing procedures suffer from known limitations. This report addresses issues in finite element human body models in evaluating pedestrian and occupant crash safety measures. A review of material properties of soft tissues and characterization methods show a scarcity of material properties for characterizing soft tissues in dynamic loading. Experiments imparting impacts to tissues and subsequent inverse finite element mapping to extract material properties are described. The effect of muscle activation due to voluntary and non-voluntary reflexes on injuries has been investigated through finite element modelling.     

Creating the brain and interacting with the brain: an integrated approach to understanding the brain

In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop.     

Lean practices implementation and their relationships with operational responsiveness and company performance: an Italian study

Although many firms report large benefits from lean implementation, a lot of scepticism still remains regarding attainable results and the possibility to apply Lean approach outside high-volume manufacturing and stable context. In this work, combining field interviews with literature review, theoretical connections have been developed among Lean manufacturing techniques, operational responsiveness and company growth performances. A conceptual model has been proposed for investigating the network of influences among lean practices (supplier management, human resource management, just-in-time and total quality management practices), operational responsiveness (Product mix variety, Product innovation and Time effectiveness) and company growth performances in Italian companies. Using structural equation modelling, a second-order confirmatory factor analysis has been used to test the hypothesised relationships in the structural models. This study highlights that the operational responsiveness is only partially connected to a Lean strategy of a company. Indeed, the lean practices implementations are negatively influenced by product mix variety and innovation, while positively influenced by time effectiveness variables. Moreover, product mix variety and time effectiveness are the main characteristics of the operational responsiveness that positively influences company growth performances. So time effectiveness could be considered as a mediator between Lean best practices and firm growth. Moreover, no direct relationship has been found between lean bundles and firm’s performances. Lack of resources and mainly poor communication and managers’ commitment and support seem to be the main obstacles of lean implementation and success.     

On the migration and trapping of single self-interstitial atoms in dilute and concentrated Fe–Cr alloys: Atomistic study and comparison with resistivity recovery experiments

Atomistic simulations have been used to characterize the mobility of single self interstitial atoms (SIAs) in Fe–Cr alloys of different compositions. Density functional theory (DFT) results concerning the interaction energies between an SIA and Cr atoms in different configurations and relative positions have been extended to concentrated alloys by using an empirical potential (EP). This EP, fitted to a set of DFT data so as to provide a correct heat of mixing and point defect features, has been further validated. Static calculations using the EP allowed the existence of configuration traps for SIAs to be identified and their strength and concentration to be assessed. Dynamic simulations were used to estimate the diffusion coefficient of the SIA, as well as to characterize the primary damage state after low-temperature electron irradiation (1–5 MeV), in Fe–Cr alloys of different Cr content. The results correlate with available experimental data and provide a qualitative and partially also quantitative explanation for the observed differences in the resistivity recovery stages in diluted and concentrated Fe–Cr alloys of different composition.     

Yearly simulation of the interaction between an ice rink and its refrigeration system: A case study

A transient model of airflow and heat transfer in an indoor ice rink and a quasi-steady model of its refrigeration system have been coupled and used to simulate their response to the time dependent ambient conditions and operating schedule for a typical meteorological year. The results for two different cases show that it is possible to reduce significantly the time of operation of the compressors and the energy consumption of the refrigeration system by simultaneously reducing the ceiling emissivity and increasing the secondary coolant temperature without affecting the quality of the ice.     

No biological advantage with a low temperature curing versus a conventional bone cement: an experimental, mechanical and histomorphometrical study in the rabbit tibia

Both tibial marrow cavities of 12 rabbits were evacuated and filled with curing bone cement. In one of the tibias conventional curing bone cement (Simplex P®) was injected, while the other tibia of the same animal was filled with a low temperature curing bone cement (Boneloc®). Three titanium implants were inserted along the proximal metaphysis of each tibia. Eight weeks after insertion the most distal implant in each tibia was removed while recording the removal torque. The implant was then once again screwed home into its bone bed. The animals were sacrificed 16 weeks after implant insertion. The previously removed implant and another implant in each tibia were then both removed while recording the removal torque. The third implant in each tibia was cut out en bloc with surrounding tissue and processed for ground section. We found no statistical differences in the mechanical or the histomorphometric evaluation of implant integration between the two cements, indicating that the low temperature curing bone cement does not result in a significantly different bone response from that of a conventional acrylic cement. ©©1999©Kluwer Academic Publishers     

Numerical study for the effects of thermophoresis and variable thermal conductivity on heat and mass transfer over an accelerating surface with heat source

A modified numerical solution scheme, for local similarity boundary layer analysis, is used to study the effects of thermophoresis and variable thermal conductivity on heat and mass transfer over an accelerating surface with heat source in the presence of suction and blowing. This numerical scheme is efficient and accurate and it can be programmed and applied easily and its application is illustrated, step by step, by studying the above mentioned problem. The resulting boundary layer equations are solved numerically by Chebyshev finite difference method. Numerical results for the velocity, temperature and concentration as well as for the skin friction, Nusselt and Sherwood numbers are obtained and reported graphically for various parametric conditions to show interesting aspects of the solution.     

A route toward the development of 3D magnetic scaffolds with tailored mechanical and morphological properties for hard tissue regeneration: Preliminary study

A basic approach toward the design of three-dimensional (3D) rapid prototyped magnetic scaffolds for hard-tissue regeneration has been proposed. In particular, 3D scaffolds consisting of a poly(ε-caprolactone) (PCL) matrix and iron oxide (Fe₃O₄) or iron-doped hydroxyapatite (FeHA) nanoparticles were fabricated through a 3D fibre deposition technique. As a first approach, a polymer to nanoparticle weight ratio of 90/10 (wt/wt) was used. The effect of the inclusion of both kinds of nanoparticles on the mechanical, magnetic, and biological performances of the scaffolds was studied. The inclusion of Fe₃O₄ and FeHA nanoparticles generally improves the modulus and the yield stress of the fibres if compared to those of neat PCL, as well as the modulus of the scaffolds. Micro-computed tomography has confirmed the possibility to design morphologically-controlled structures with a fully interconnected pore network. Magnetisation analyses performed at 37°C have highlighted M-H curves that are not hysteretic; values of saturation magnetisation (M_s) of about 3.9 emu/g and 0.2 emu/g have been evaluated for PCL/Fe₃O₄ and PCL/FeHA scaffolds, respectively. Furthermore, results from confocal laser scanning microscopy (CLSM) carried out on cell-scaffold constructs have evidenced that human mesenchymal stem cells (hMSCs) better adhered and were well spread on the PCL/Fe₃O₄ and PCL/FeHA nanocomposite scaffolds in comparison with the PCL structures.