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.     

Information technology and structural change in the paper and pulp industry : Some technological, organizational and managerial implications

The paper and pulp industry has experienced a structural change during the last 15 years. The products have differentiated and completely new paper types have been introduced. The standard and classical products, like news print paper, are often specialized and customized versions from the standard product in order to fulfill the specific needs of different printing processes better. These changes have impacted on the production organization and structures of enterprises. The key companies have acquired more production capacity in different countries and have become really international companies. These trends are likely to continue. One of the technological driving forces has been the applying of information technology. The digital process automation systems as well as the mill wide information systems have been strategic tools and technological corner stones in the structural change. However, it is only technology which matters. Also new organisational forms as well as new implementation methods of systems are needed.     

Design by customer: concept and applications

Customer satisfaction can be increased by reducing the gap between what customer really needs (customer requirements) and what manufacturer can provide (product specifications). The approach of Design for Customer where products are generated by translating customer needs into product specifications (in mass production system) or into product variety (in mass customization system) is not able to give optimum satisfaction to all customers. Some customers are still forced to relax their requirements and to accept predefined product in the assortment. This study proposes a new concept of Design by Customer to increase customer satisfaction by opening maximum possible channel for customers to involve in value creation so that they are no longer only searching for goods but they can also, when necessary, involve in production cycle to specify their own design. In order to ensure the viability of the proposed concept, the integration of multi customer involvement decoupling point, product attribute analysis, crowdscreening and new manufacturing strategy are introduced in this paper. Real products of resin-based table clocks are used as practical example to verify the concept applicability and to demonstrate its merit.     

An overview of workflow management: From process modeling to workflow automation infrastructure

Today's business enterprises must deal with global competition, reduce the cost of doing business, and rapidly develop new services and products. To address these requirements enterprises must constantly reconsider and optimize the way they do business and change their information systems and applications to support evolving business processes. Workflow technology facilitates these by providing methodologies and software to support (i) business process modeling to capture business processes as workflow specifications, (ii) business process reengineering to optimize specified processes, and (iii) workflow automation to generate workflow implementations from workflow specifications. This paper provides a high-level overview of the current workflow management methodologies and software products. In addition, we discuss the infrastructure technologies that can address the limitations of current commercial workflow technology and extend the scope and mission of workflow management systems to support increased workflow automation in complex real-world environments involving heterogeneous, autonomous, and distributed information systems. In particular, we discuss how distributed object management and customized transaction management can support further advances in the commercial state of the art in this area. Recomended by: Omran Bukhres and e. Kühn     

A novel approach to conduct the importance-satisfaction analysis for acquiring typical user groups in business-intelligence systems

Business intelligence (BI) is a powerful tool to conduct causality analysis and corporate diagnoses since it provides a data-driven approach to link firms' strategic goals into tactical policies and operational actions. Specifically, BI consists of a series of architectures and techniques like database, data warehousing, and data mining that transform raw data into useful information to provide decision supports. In reality, typical BI user groups involve financial analysts, marketing planners, general managers, field staffs, upstream suppliers, and downstream customers. Inspired by the concept of STP (segmentation-target-positioning) and product family design, BI systems need to be customized to satisfy diverse user groups and tailored to a firm for solving complicated but specific business problems. Consequently, a novel framework is proposed to fulfill the following goals: (1) incorporating user preferences to identify key design features that best fit BI's main segments for achieving customer acquisition, (2) transforming user perceptions into quantitative degrees of satisfaction for accomplishing customer retention, and (3) conducting the importance-satisfaction analysis to generate managerial insights for developing next-generation BI systems.     

Whole-body collision avoidance control design using quadratic programming with strict and soft task priorities

Despite safe mechanical design is necessary for the collaborative robots, we can not underestimate the importance of active safety due to a multi-objective control design. Active safety not only complements the mechanical compliance but also enables classical industrial robots the ability to fulfill additional task-space objectives. Using the gradient of the collision avoidance task as hard constraints of a quadratic programming (QP) controller, we assign strict priority to avoid collisions and specify other QP controller objectives with soft task priorities. Through experiments performed on a dual-arm robot, we show that the proposed solution is able to generate safe robot motion that fulfills the task specifications while keeping the feasibility of the underlying quadratic optimization problem.     

A clustering approach for modularizing service-oriented systems

Journal of Intelligent Manufacturing - Companies are seeking more and more to offer customized goods and services to customers to be able to satisfy their needs. Several methods emerged to fulfill...     

面向3D虚拟展示的软件定制化系统研究

针对传统三维虚拟展示软件中存在的编程过程复杂、开发周期长等缺陷,提出一个具有可定制性和扩展性面向虚拟展示的定制方法。该方法基于虚拟现实技术和软件大规模定制技术,设计面向虚拟展示的定制化系统架构;基于软件功能树对系统功能解耦,抽取可复用的公共模块实现参数定制化,封装为功能接口供系统调用;同时定义了系统的定制模板,以描述和配置应用系统的基本信息和个性化定制,从而满足不同企业产品虚拟展示功能定制需求。最后通过具体实例展示验证了该系统的有效性和实用性。     

Customizability analysis in design for mass customization

Product customization has been recognized as an effective means to implement mass customization. This paper focuses on the customizability issue of design, that is, to evaluate the cost effectiveness of a design to be customized in order to meet individual customer needs. Three aspects of customizability are identified, namely, (1) design customizability: the intrinsic nature of product by design, which renders customization to be easy or deficient for either customers or the manufacturer, (2) process customizability: the economic latitude of (production) process variations due to product customization, and (3) the value of customization as perceived by the customers. While design customizability is measured based on the information content metric, the evaluation of process customizability follows the general gist of process capability indices. Conjoint analysis is employed to explore customer preference for multiple product features in terms of utility. Customizability analysis thus exhibits a maximization of customer-perceived value while exploiting the potential of design to be customized by achieving optimal design and process customizability indices.     

RMS design methodology for automotive framing systems BIW

Today, markets increasingly require more customized products, with shorter life cycles. In response, manufacturing systems have evolved from mass production techniques, through flexible automation and mass customization, to produce at mass production costs. Manufacturing facilities must incorporate more flexibility and intelligence, evolving toward reconfigurable manufacturing systems (RMS). RMS are amid to posses such flexibility and responsiveness and said to be the next generation of world class systems. RMS are designed for rapid change in structure and for a quickly adjustable production capacity. This paper proposes a new methodology (high level process) of framework using flexible and reconfigurable manufacturing systems principles for automotive framing systems as well as to provide a guideline to support the structure of different stages of the design methodology. The proposed methodology is presented through a case study using data based on actual production systems of three different styles; (process and design data) which supports the hypothesis of the research.     

Segmenting customers in online stores based on factors that affect the customer’s intention to purchase

This study has proposed an approach that enables online stores to offer customized marketing by segmenting their customers based on customers’ psychographic data. Online stores can concentrate on more profitable activities by identifying customers’ value as they segment their customers into a few groups of customers with similar intentions to purchase. To segment online customers, based on previous research that explains the behavior of online customers regarding purchasing, the approach has employed the factors that affect the customers’ intention to purchase on the Web. We integrated the clustering results of SOM (self-organized map) and the k-means algorithm into a single model. Online stores can develop promotional marketing and offer personalized service for e-customers, who are more valuable and more promising, according to the market segments presented by our approach.     

Resource planning for direct fabrication of customized orthopedic implants using EBM technology

Medical innovations and patient expectations are pushing healthcare toward personalized medicine. In orthopedics, the concept of patient-specific implants could be economically realized with the use of additive manufacturing. Knee and hip replacements are some of the most common musculoskeletal procedures performed in the United States. Joint replacement implants are typically offered in standard sizes and geometries. The mass customization of theses prostheses, however, can improve patient outcomes and reduce medical costs. Mass customization is not economically feasible with traditional manufacturing methods because of the high fixed tooling costs for each geometry. The freedom of design offered by additive manufacturing presents a viable production alternative for unique personal geometry. The objective of this paper is to develop two new analytic models that can be used to investigate a complex additive manufacturing supply chain. The focus of the model is to provide planning tools and a methodology for the direct production of customized orthopedic implants using electron beam melting, an additive manufacturing technology. First, a production model for an additive manufacturing-based system is created. Next, resource planning for a single customized implant system is performed using a simulation model. A queuing model is developed for rapid systems analysis. The staffing requirement predictions of the two models align closely for production of a singular, customized implant. A detailed systems analysis of an additive manufacturing supply chain is conducted to illustrate the use of these models. The queueing model is analytically tractable, so it is extended to describe the production of standard and customized versions of multiple implant families.     

Personalised Product Recommendation Model Based on User Interest

The scale of e-commerce systems is increasing and more and more products are being offered online. However, users must find their own desired products among a large amount of unrelated information, which makes it increasingly difficult for them to make a purchase. In order to solve this problem of information overload, and effectively assist e-commerce users to shop easily and conveniently, an e-commerce personalized recommendation system technology has been proposed. This paper introduces the design and implementation of a personalized product recommendation model based on user interest. The “shopping basket analysis” functional model centered on the Apriori algorithm uses the sales data in the transaction database to mine various interesting links between the products purchased by the customers. Moreover, it helps merchants to formulate marketing strategies, reasonably arranges shelf-guided sales, and attracts more customers. This platform adopts a B/S structure and uses JSP+AJAX technology to achieve the dynamic loading of pages. In the background, the Struts2 framework is combined with the SQL Server database to establish the system function module, and then the function is gradually improved according to the requirement analysis, and the development of the platform is finally completed.     

基于协同过滤算法的微信小程序智能助手

随着信息技术和网络的不断迅猛发展,互联网的信息资源急剧增长.信息过载问题促进了个性化推荐技术发展.协同过滤算法通过在用户和信息之间建立联系,被广泛应用于电子商务各个领域.本文提出通过利用微信小程序来获取用户的个性化信息数据,并且通过协同过滤算法,为用户设计的微信小程序智能助手,能够为用户推荐符合用户个性化的生活服务信息.在本文中,介绍了智能助手的设计方法,并详细介绍了系统的功能和个性化推荐功能的实现.     

Product architecting for personalization

Personalization is an emerging manufacturing paradigm whereby customers can tailor products to their individual needs while maintaining high production efficiency. This paradigm necessitates “personalized product architecting” for determination of customizable/personalizable product modules and cost-effective manufacturing methods. This paper presents an initial effort in developing a method for identifying appropriate product architectures and manufacturing resolutions to achieve personalization considering functional utility and manufacturing cost. Ergonomic experiments and conjoint analysis are implemented to build functions relating manufacturability, price, and utility. Using these functions, a case study based on shoe products is conducted and the common integer programming welfare problem is expanded to a mixed-integer programming optimization problem for determination of a product family incorporating both personalized and customized offerings.     

Intelligent agent-based systems for personalized recommendations in Internet commerce

The prosperity of electronic commerce has changed the traditional trading behaviors and more and more people are willing to conduct Internet shopping. However, the exponentially increasing information provided by the Internet enterprises causes the problem of overloaded information, and this inevitably reduces the customer's satisfaction and loyalty. One way to overcome such a problem is to build personalized recommender systems to retrieve product information that really interests the customers. For products that people may purchase relatively often, such as books and CDs, recommender systems can be built to reason about a customer's personal preferences from his purchasing history and then provide the most appropriate information services to meet his needs. On the other hand, for those commodities a general customer does not buy frequently, for example computers and home theater systems, more appropriate are the kinds of recommender systems able to retrieve optimal products based on the customer's current preferences obtained from the iterative system–customer interactions. This paper presents the above two kinds of recommender systems we have developed for supporting Internet commerce. Experimental results show the promise of our systems.     

Powering E-Learning In the New Millennium: An Overview of E-Learning and Enabling Technology

In today's new economy characterized by industrial change, globalization, increased intensive competition, knowledge sharing and transfer, and information technology revolution, traditional classroom education or training does not always satisfy all the needs of the new world of lifelong learning. Learning is shifting from instructor-centered to learner-centered, and is undertaken anywhere, from classrooms to homes and offices. E-Learning, referring to learning via the Internet, provides people with a flexible and personalized way to learn. It offers learning-on-demand opportunities and reduces learning cost. This paper describes the demands for e-Learning and related research, and presents a variety of enabling technologies that can facilitate the design and implementation of e-Learning systems. Armed with the advanced information and communication technologies, e-Learning is having a far-reaching impact on learning in the new millennium.     

浅谈宽带客户双路由接入模式的保障与实现

伴随着整体电信网络的发展,中国企业信息化进程加速,企业网大客户接入市场规模不断扩大,呈现出网络向全光化发展;产品向定制化、个性化、智能化及综合化发展;服务向精细化发展等趋势,由于企业用户需求复杂,通常宽、窄带业务,话音、数据业务需求并存,网络配置灵活性要求高,定制需求强,相应的适应企业客户需求的综合接入设备与一般公众接入网络有很多区别,形成了一个以客户需求为导向的高端市场如企业、政府和金融单位。本文浅析了运营商为宽带客户进行双路由接入的几种模式,并进行了比较,作为接入方案制定的参考。     

Product mix strategy and manufacturing flexibility

The manufacturing industry is facing a turbulent and constantly changing environment, with growing complexity and high levels of customisation. Any investment solution should address these problems for a dynamic market and within limited budget boundaries, so that companies try to remain competitive. The authors propose a real options model to support firms making important investment decisions, specifically decisions associated with the acquisition of new equipment aimed at allowing firms to increase their manufacturing flexibility for the production of both standard and customized products. This paper is partially based on a real operating experience related to visual finishing technology features in an industrial company that conforms to the definitions of the product mix. The authors’ motivation for this work is driven by firms’ desire to satisfy specific customer needs, and to respond to them quickly under uncertain demand. Our goal, using theories from finance, production management, and product offering management, is to conclude that there is a relevant difference between the evaluation of the technology that is to be chosen, and the potential value due to product mix adaptations that are able to provide the maximum return from investment. We address problems related to standard and customized production systems, and the decision to invest in a set of resources that will enable this choice.     

An agent-based recommender system for developing customized families of products

Electronic markets and web-based content have improved traditional product development processes by increasing the participation of customers and applying various recommender systems to satisfy individual customer needs. Agent-based systems based on agents’ roles and tasks can provide appropriate tools to solve product design problems by recommending design knowledge and information. This paper introduces an agent-based recommender system to support designing families of products based on customers’ preferences in dynamic electronic market environments. In the proposed system, a market-based learning mechanism is applied to determine the customers’ preferences for recommending appropriate products to customers of the product family. We demonstrate the implementation of the proposed recommender system using a multi-agent framework. Through simulated experiments, we illustrate that the proposed recommender system can help determine the preference values of products for customized recommendation and market segment design in various electronic market environments.