Integrated product and manufacturing system platforms supporting the design of personalized medicines

Pharmaceutical product customization, a prerequisite for personalized medicines, is currently a widely researched topic. Patient characteristics can be mapped and translated into parameters for designing patients’ individual treatment, i.e., the dosage form. However, current pharmaceutical manufacturing is dominated by mass production and lacks the capability and flexibility required to produce customized products. Mass customization is a proven successful approach in, for example, the manufacturing industry and thus has been discussed as an enabler for pharmaceutical product customization but has never been fully explored in a pharmaceutical context. Inspired by mass customization approaches in the manufacturing industry, this study proposes a novel methodology to develop integrated product and manufacturing system platforms for pharmaceutical products supporting a mass customization paradigm. The proposed methodology establishes sets of product and manufacturing system platform variants and suggests an approach to feasible platform design selection. The applicability of the proposed methodology is illustrated for diabetes treatment as a selected case example. Integrated platform designs are developed for the conventional treatment of a fully integral tablet design and for a design enabling product customization with a modularized tablet design. The manufacturing platforms are still embracing a mass production design in the methodology illustration and should elicit knowledge on the utility of the current production design in a mass customization context. The performance and utility of the respective platform are assessed in terms of production cost and patient benefit. The results suggest a substantial increase in patient benefit afforded by the modularized tablet design, however the production cost is increased. This trade-off between the production cost and patient benefit thus calls for novel manufacturing system concepts to achieve the feasible manufacturing of customized pharmaceutical products.     

Extended object model for product configuration design

This paper presents an extended object model for case-based reasoning (CBR) in product configuration design. In the extended object model, a few methods of knowledge expression are adopted, such as constraints, rules, objects, etc. On the basis of extended object model, case representation model for CBR is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of CBR in product configuration design, such as case representation, indexing, retrieving, and case revising. The presented model is an extension of the traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, and solution class used in case revising. Therefore, the product configuration knowledge used in the product configuration design can be represented by using this model. In the end, a metering pump product configuration design system is developed on the basis of the proposed product configuration model to support customized products.     

Semantic Web based innovative design knowledge modeling for collaborative design

This paper describes a study about how to use the Semantic Web technologies for innovative design knowledge modeling in a multi-agent distributed design environment. Semantic Web based knowledge modeling for innovative design is proposed as prelude to the meaningful agent communication and knowledge reuse for collaborative work among multidisciplinary organizations. A model for innovative design is proposed at first, based on which a knowledge schema is brought forward. For sharing the design knowledge among an internet-based or distributed work team, even globally, A RDF-based knowledge model is presented to realize its representation on Semantic Web. A Semantic Web based repository for innovative design and its API for topper Semantic Web applications have been also constructed. The proposed knowledge modeling extends traditional product modeling with capabilities of innovative design, knowledge sharing and distributed problem solving, and is employed as a content language within the messages in the proposed multi-agent system architecture. The proposed approach is viewed as a promising knowledge management method that facilitates the implementation of computer supported cooperative work in innovative design of Semantic Web applications.     

A distributed and interactive system to integrated design and simulation for collaborative product development

The goal of applying collaborative product development in industry has raised the need to develop software tools supporting system integration and group collaboration. Current methods and tools mainly focus on the collaborative creation of design components and assemblies. However, few of them support the collaborative work in developing simulation models so that proposed design concepts and solutions can be evaluated by integrating expertise from several disciplines. The purpose of this research is to develop a distributed and interactive system on which designers and experts can work together to create, integrate and run simulations for engineering design. To develop such a system, a number of issues, e.g. effectiveness and efficiency of modeling work, the re-use of models, interaction and cooperation, accuracy of simulation, collaborative operation on models, etc., need to be addressed. This paper describes an open architecture to developing simulations for engineering design in a distributed and collaborative environment, identifies a set of key issues raised in this architecture, and presents the techniques employed in our solution.     

An ontology-based support for product conceptual design

The research presented in this paper is a follow-up of our prior work involving the development of a graphical modeling tool to support designers at the conceptual design stage. To close the loop for supporting designers in generating design concepts flexibly, fast, and easily, an ontology-based approach for knowledge management that works along with the graphical modeling tool is discussed. Ontology and databases for the tool are developed to promote the systematic capture of design knowledge and efficient reuse of the design knowledge selection. In order to locate the proper information and query the data from the databases, the relationship between the ontology and databases, the data analysis process, ontology enrichment, and the ontology-based query engine are built to offer users multiple design results according to users’ requirements. A tire design example is presented to demonstrate the proposed approach. The ontology-based method described in this paper can help retrieve and save the complex relations, support the reasoning, integrate heterogeneous data resources and offer users more accurate, proper and comprehensive data.     

基于模糊综合评价的交互式产品设计应用与研究

交互式产品设计能给用户带来人和产品之间双向信息交流的体验,它除了实现产品本身的功能外,其交互设计能否最大限度地令用户对产品易用、乐用和高效应用是产品的重要评判标准。借用模糊数学中的模糊综合评价方法,综合考虑交互式产品设计各因素,结合用户体验,建立交互式产品设计评价的数学模型;按模糊矩阵的运算方法和最大隶属原则得到综合评价结果;实现从定性到定量,最终又回到定性的转化,为产品的决策提供可靠依据。     

Mereotopological assembly joint information representation for collaborative product design

In this paper we discuss an ontology-based representation method for differentiating assembly joints in collaborative and intelligent product design. As design becomes increasingly knowledge-intensive, intelligent, and collaborative, the need becomes more critical for computational frameworks that enable product development by effectively supporting the formal representation, capture, retrieval, and reuse of product knowledge. Joints are a key aspect of assembly models that are often ambiguous when model sharing takes place. Although various joints may have similar geometries and topologies, the physical implications of the selected joining processes may vary significantly. It is possible to attach notes and annotations to geometric entities in order to distinguish joints; however, such textual information does not readily prepare the model for downstream activities, such as simulation and analysis. As an illustration, analysts must read and interpret the annotations in order to develop the appropriate boundary conditions. In this work, we present an assembly design ontology that explicitly represents assembly constraints, including joining constraints, and infers any remaining implicit ones. By relating concepts through ontology technology rather than just defining data syntax, assembly and joining concepts can be captured in their entirety or extended as necessary. By using the knowledge captured by the ontology, similar looking joints can be differentiated. For this research, we used a mereotopology, which is a region-based theory for parts, and the Semantic Web Rule Language (SWRL) to represent the difference of joints and to define assembly design terms and their relationships. We also used SWRL so that the joining rules can be reasoned to differentiate assembly joints. Finally, by using an ontology, various geometrically and topologically similar joints are successfully differentiated in a standard and machine-interpretable manner.     

Chemical enterprise model and decision-making framework for sustainable chemical product design

The chemical product substitution process is undertaken by chemical industries for complying with regulations, like REACH in Europe. Initially devoted to chemists, chemicals substitution is nowadays a complex process involving corporate, business and engineering stakeholders across the chemical enterprise for orienting the search toward a sustainable solution. We formalize a decision making process framework dedicated to the sustainable chemical product design activity in an industrial context. The framework aims at improving the sharing of information and knowledge and at enabling a collaborative work across the chemical enterprise stakeholders at the strategic, tactical and operational levels. It is supported by information and communication technologies (ICT) and integrates a computer aided molecular design tool. During the initial intelligence phase, a systemic analysis of the needs and usages enables to define the product requirements. In the design phase, they are compiled with the help of a facilitator to generate the input file of a computer aided product design tool. This multiobjective tool is designed to find mixtures with molecular fragments issued from renewable raw materials, and is able to handle environment-health and safety related properties along with process physicochemical properties. The final choice phase discusses the solution relevancy and provides feedback, before launching the product manufacturing. The framework is illustrated by the search of a bio-sourced water–solvent mixture formulation for lithographic blanket wash used in printing industry. The sustainability of the solution is assessed by using the sustainability shades method.     

基于Petri网的机电产品概念设计功能模型研究

功能分析是概念设计中最重要的阶段,从黑箱法的理论出发,以流及其状态和功能为基本要素建立了基于Petri网的机电一体化产品概念设计功能模型,为产品概念设计过程的优化以及设计效率的提高打下了良好基础,为以后智能软件的开发提供了良好的模型.     

基于特征点加细的多分辨率人脸形变模型及人脸建模

提出基于特征点加细的原型三维人脸对应方法建立多分辨人脸形变模型,并根据该形变模型的特点使用多分辨模型匹配方法由单张正面人脸图像进行三维人脸建模。该方法以人脸模型上的眼、眉、口、鼻等主要几何特征为基准点标注基础网格,然后通过加细特征点网格完成原型人脸之间的对应,进而建立多分辨率的形变模型;根据形变模型的构造特点,把待匹配图像按照与模型相同方式进行加细,然后进行多分辨的人脸模型匹配。实验结果表明,新的对应算法可以有效地实现原型三维人脸之间的对应,能够克服传统的光流对应算法对应效果差,算法精度低的缺陷,提高形变模型的精度。新的匹配算法不仅能够加速模型的匹配速度,而且可提高模型匹配的效率和精度,缩短模型匹配的时间。     

Wearable sensors for 3D upper limb motion modeling and ubiquitous estimation

Human motion capture technologies are widely used in interactive game and learning, animation, film special effects, health care, and navigation. Because of the agility, upper limb motion estimation is the most difficult problem in human motion capture. Traditional methods always assume that the movements of upper arm and forearm are independent and then estimate their movements separately; therefore, the estimated motion are always with serious distortion. In this paper, we propose a novel ubiquitous upper...     

A CSP approach for the network of product lifecycle constraints consistency in a collaborative design context

In this paper, we are considering that the design process can be modelled in the form of a constraint satisfaction problem (CSP). CSP modelling or resolution has proved its efficiency within the framework of single-designer design. We propose to extend the functions of CSP to the context of multi-concept design of the same artefact. We define CoCSP as cooperative constraint satisfaction problem including the actors of the design problem. We are presenting the operating principles of an algorithm for the real-time management of design decisions, based on a model described in the form of a CoCSP for the integration of supply-chain constraints. This algorithm enables the number of design decisions rejected at a given moment in design to be kept to a minimum. The algorithm forms the core of a prototype for an unsupervised, generic constraint-based collaborative design system. Our aim is to produce a platform centred on the notion of constraints that will enable a product design problem to be modelled and solved by integrating supply-chain constraints as far upstream as possible.     

Integrated product and process design: a multi-objective modeling framework

In this paper we present an analytical multi-objective framework for the concurrent design of product and processes. The objective is to simultaneously consider the tolerance specification on the product or the component dimensions along with the selection of the manufacturing processes. For this purpose we consider three objectives: to minimize unit cost, to minimize quality loss and to minimize manufacturing lead time. We characterize the properties of the non-dominated solutions. These solutions provide flexibility needed in an agile manufacturing environment. The min–max approach is used to obtain trade-off solutions.     

基于单张图像的三维人脸建模与表情动画

在人机交互、数字娱乐等领域,传统的表情合成技术难以稳定地生成具有真实感的个性化人脸表情动画.为此,提出一种基于单张图像的三维人脸建模和表情动画系统.自动检测人脸在图像中的位置,自动定位人脸上的关键点,基于这些关键点和形变模型重建个性化三维人脸模型,对重建的人脸模型进行扩展得到完整的人脸网格,采用稀疏关键点控制的动画数据映射方法来驱动重建的人脸模型生成动态表情动画.实验结果表明,该方法稳定性强、自动化程度高,人脸模型与表情动画比较逼真.     

A product configuration analysis method for emotional design using a personal construct theory

Identifying emotion-related product attributes (perceived by consumers) is no easy task in the realm of emotional design. Conventionally, this process relies heavily on the researchers who conduct the Kansei experiments selecting product attributes such as color, form, and texture for Kansei studies. However, in so doing, other product attributes that also play a vital role in product-emotion associations might be neglected by the researchers. More importantly, the identification of product attributes should be based on consumer's point of view (and feelings). Accordingly, a personal construct theory based product configuration analysis method is proposed in this work. The method develops the customer's mind map for each Kansei tag in order to capture replications of candidate products. A means-value chain is used to generate targets which are later compared with candidate products by consumers. The comparison results could suggest product attributes that are relevant to the desired Kansei. The proposed approach is presented and illustrated using a case study of Graffiti designs on notebooks. Results obtained are discussed. It appears that the proposed method is promising in identifying product attributes with desired Kansei impacts.     

基于Inventor API的家具三维造型设计

国内外家具业趋向于设计出不同系列风格的家具,同时又要求提高设计效率.为了能够满足这方面的需要,通过研究Inventor API的功能,关联Inventor与数据库Excel,运用Inventor的二次开发工具Autodesk Inventor Wizards,基于VB.NET实现了对话框界面的通讯机制,即实现人机交互界面以达到程序自动建模的功效.从已有的家具模版中自动地生成新的家具,并能够替换整体家具的零部件,大大地提高了设计效率,实现并给出了程序示例.快速、自动地新建家具模型的结果表明,基于Inventor API的技术在家具三维造型设计二次开发中具有重要的意义.     

基于概率支持向量回归的产品设计时间预测模型

为使产品设计时间预测既克服小样本、异方差噪声问题,又提供除预测值以外的其他有用信息,建立概率支持向量回归(PSVR)模型。首先,在异方差回归模型基础上设计概率约束条件,以使预测值以较大概率位于真实值的某邻域,结合具有参数不敏感损失函数的支持向量回归确定优化目标,提出PSVR。然后,将最大完工时间知识嵌入进PSVR的约束条件,用以确定真实值邻域的宽度,将交叉验证与遗传算法相结合以确定PSVR的相关参数。最后,以注塑模具设计的实例进行分析,结果表明基于PSVR的时间预测方法可同时提供有效的预测值和预测区间。     

基于本体和粗糙集的协同产品设计知识约简

协同产品设计具有知识来源广、知识类型复杂多样等特点。为简化产品设计知识库并从中有效地提取出对产品设计人员有价值的知识,提出了基于本体和粗糙集的协同产品设计知识约简方法。首先通过引入本体技术对设计知识进行本体建模、显式定义语义和统一表达,以增加产品设计知识的语义;然后通过决策属性的正域及核求解等知识约简方法将设计知识库中对设计人员不重要的、冗余的知识进行约简,精练设计知识库,分析并求解出了约简后知识库中知识的依赖度,从而为设计人员选取与设计密切相关的知识提供依据。最后以汽车发动机的协同设计为例介绍了本文的方法。     

Rough set and PSO-based ANFIS approaches to modeling customer satisfaction for affective product design

Facing fierce competition in marketplaces, companies try to determine the optimal settings of design attribute of new products from which the best customer satisfaction can be obtained. To determine the settings, customer satisfaction models relating affective responses of customers to design attributes have to be first developed. Adaptive neuro-fuzzy inference systems (ANFIS) was attempted in previous research and shown to be an effective approach to address the fuzziness of survey data and nonlinearity in modeling customer satisfaction for affective design. However, ANFIS is incapable of modeling the relationships that involve a number of inputs which may cause the failure of the training process of ANFIS and lead to the ‘out of memory’ error. To overcome the limitation, in this paper, rough set (RS) and particle swarm optimization (PSO) based-ANFIS approaches are proposed to model customer satisfaction for affective design and further improve the modeling accuracy. In the approaches, the RS theory is adopted to extract significant design attributes as the inputs of ANFIS and PSO is employed to determine the parameter settings of an ANFIS from which explicit customer satisfaction models with better modeling accuracy can be generated. A case study of affective design of mobile phones is used to illustrate the proposed approaches. The modeling results based on the proposed approaches are compared with those based on ANFIS, fuzzy least-squares regression (FLSR), fuzzy regression (FR), and genetic programming-based fuzzy regression (GP-FR). Results of the training and validation tests show that the proposed approaches perform better than the others in terms of training and validation errors.