Search

This paper presents the idea of supporting product inspection planning process during the early stages of product life cycle for the experts working on product development. Aim of this research is to assist a collaborative product development process by using Smart Virtual Product Development (SVPD) system, which is based on Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). The proposed system is developed to support three key aspects of industrial product development i.e. design, manufacturing, and product inspection. Therefore, it comprises of three main modules; design knowledge management (DKM), manufacturing capability and process planning (MCAPP), and product inspection planning (PIP). It collects, stores, and uses experiential knowledge from formal decisional events in the form of set of experience (SOE). This research enlightens the working mechanism of the PIP module, and shows how experiential knowledge related to product inspection can be used during the early stages of product development process. This experiential knowledge is extracted and stored from similar products having some common features and functions. First, the basic description and principles of the approach are introduced, then the prototype version of the system is developed and tested for product inspection planning (PIP) module for the case study, which verifies the feasibility of the proposed approach. The presented system successfully supports smart manufacturing and can play a vital role in Industry 4.0.

The South Korean government is actively assisting the supply of the smart factory solutions to SMEs (Small & Medium-sized Enterprises) according to its manufacturing innovation 3.0 policy for the smart manufacturing as the 4th industrial revolution era unfolds. This study analyzed the impacts of the smart factory solutions, which have been supplied by the government, on the companies performances. The effects of the level of smart factory and the operation capabilities for the smart factory solutions on company performances, and the mediating effects of manufacturing capabilities have been analyzed using SPSS and AMOS. The data for this survey-based study were collected from the SMEs which implemented the smart factory solutions since 2015. The results show that the level of smart factory solutions adopted and operation capabilities for the smart factories do not have direct effects on the company performances, but their mediating effects on the manufacturing capabilities matter and the manufacturing capabilities effect directly on the company performances. In addition significant factors boosting the operation capability for the smart factory and the levels of the smart factory solutions are identified. Finally, the policy direction for enhancing the smart factory effects is presented, and the future research directions along with the limitations are suggested.

This paper aims to investigate the manufacturing strategies for the manufacturing systems in the context of 3D printing, referring to ecosystem-based manufacturing systems, rather than firm-based and network-based ones. A case study approach was adopted for this research, as the data was mainly collected via semi-structured interviews with staff members of companies in China. Besides the elements of strategic choices and manufacturing capabilities identified in the extant literature, this research verified three additional strategic choice elements (functional role, platform and solution) and identified two factors (platform openness and solution diversity) to classify an ecosystem-based manufacturing system. Meanwhile, four manufacturing capabilities of the ecosystem-based manufacturing system have been identified: collaborative manufacturing flexibility, rapid thriftiness ability, self-customisation and co-evolved design capability. This research results contribute to the area of manufacturing strategy via expanding its view from the firm and network levels to the ecosystem level. Meanwhile, the research results present operations managers with an understanding of the strategic choices and manufacturing capabilities of an ecosystem-based manufacturing system in the context of 3D printing.

In the past few years, additive manufacturing with metal powders industry has gained rapid traction in the metal manufacturing sector, prominently in those regions where conventional manufacturing encounters limitations related to manufacturing capability and design methodology.

As a key factor for making decisions for production scheduling, manufacturing capability has been attracted great attention by academia and industries. With the increasing customized and personalized needs, modern manufacturing enterprises need to fabricate products at low cost, at right time, and at high effectiveness. Therefore, it is necessary to optimize the manufacturing system in order to improve productivity and the competitiveness of enterprises. The analysis and evaluation of manufacturing capabilities play an extremely important role in the optimal scheduling of production. In this paper, the manufacturing capability of a job shop is investigated. The indicator system is built for evaluating the manufacturing capability of a job shop and an evaluation method is proposed based on the combination of the entropy weight method and the grey relational analysis. Finally, a case study is used to validate the method.

The pressurized water reactor CAP1400 is one of the sixteen National Science and Technology Major Projects. Developed from China's nuclear R&D system and manufacturing capability, as well as AP1000 technology introduction and assimilation, CAP1400 is an advanced large passive nuclear power plant with independent intellectual property rights. By discussing the top design principle, main performance objectives, general parameters, safety design, and important improvements in safety, economy, and other advanced features, this paper reveals the technology innovation and competitiveness of CAP1400 as an internationally promising Gen-III PWR model. Moreover, the R&D of CAP1400 has greatly promoted China's domestic nuclear power industry from the Gen-II to the Gen-III level.

This research investigates the determinants of the performance of small and medium sized manufacturers on business-to-business electronic marketplaces (B2B EMs). Based on the resource-based view, the framework proposed suggests that a manufacturing firm's performance on a B2B EM is determined by EM enabling capabilities, namely the online marketing capability, flexible manufacturing capability and content management capability. Further, the framework posits that these EM enabling capabilities are in turn determined by the firm's IT capability. Data from 358 online manufacturers participating in a B2B EM is collected and analyzed. The results confirm our hypotheses that the online marketing capability, flexible manufacturing capability and content management capability fully mediate the impact of the IT capability on the firm's online performance. Furthermore, the online marketing capability is found to be a stronger factor in influencing the manufacturer's online performance than the others. Performance of manufacturers operating on B2B electronic marketplaces is studied.The model explaining the performance includes IT capability and EM enabling capabilities of the manufacturers.The research model was tested using data from 358 online manufacturers.IT capability positively affect the performance of manufacturers through the mediation of EM enabling capabilities.

Automotive industry is believed to be the pioneer in pushing the growth of manufacturing industry in Indonesia. By implementing manufacturing strategy, the industry will get its performance improved. Automotive component manufacturer is an important part of automotive industry. This research discusses the relationship between influential variables with performance in Indonesia automotive component manufacturer namely manufacturing capability and manufacturing strategy. A model is developed and data are collected from automotive component manufacturers around Jakarta area. Data is processed using Structural Equation Modeling (SEM). The result shows that manufacturing capability significantly influences manufacturing strategy while manufacturing strategy also significantly influences performance of Indonesia automotive component manufacturer.

With the development of information and computer network technology, cloud manufacturing has been developing rapidly, industrial robots (IRs) as a vital symbol and an advanced technology of manufacturing industry, in scheduling service, the constantly changing information data will result in the corresponding vary of the manufacturing capability. Under a fixed constraint of some capability service request, this will decrease the number of the optimal solutions and provide the inaccurate service to users. So it is important to make the manufacturing capability stable and obtain more optimal solutions to satisfy the constraint, thus the dynamic assessment of manufacturing capability based on information feedback is investigated in this paper. A set of indicators is established considering the IRs’ manufacturing capability and a new dynamic assessment model is proposed to achieve the actual data and the expected data information feedback, using the “normal distribution” model, which can correct the assessment weight. By the way, a case study is simulated in the MATLAB, which shows the reliability and reasonability of this method in evaluate the manufacturing capability in IR.

Manufacturing capability of a firm is given by the level of output generated by the production system employed which in turn decides the competitiveness in the market. The pattern of structural and infrastructural decisions in the manufacturing affects the capability of the production system. Therefore, it is crucial to know the overall manufacturing capability of a firm and the contribution of each decision in it. This paper presents quantification of manufacturing capability based on multi-criteria approach. A total of 33 decisions (criteria) and their corresponding choices have been identified from the literature analysis to quantify the manufacturing capability. These decisions are then classified into six decision areas (group criteria), and the manufacturing capability evaluation problem is modeled by using analytical hierarchy process (AHP) framework. The approach facilitates computation of manufacturing capability index by evaluating the decisions taken in the manufacturing, which is then mapped into four levels, namely, infant, industry average, adult, and world class as proposed by the Miltenburg. The methodology is illustrated with a numerical example for a job shop manufacturing system.

This paper discusses a method to determine optimum numbers of kanban in Just In Time production system and analyzes effect of optimum numbers of kanban to manufacturing performance. Method to determine kanban numbers was carried out by designing kanban flow based current situation, gathering relevant parameter on floor and company database, and calculating of kanban quantity through basic mathematical model. The basic mathematical model of kanban is derived according to designated kanban flow in JIT production system. The optimum number of kanbans would control and regulate material flow in manufacturing, thus JIT is achieved. As a result, product lead time and inventory stock level are improved. The conclusion is that an appropriate determination numbers of kanban could lead to optimizing manufacturing capability.

Design and manufacture of aircraft requires deep multi-disciplinary understanding of system behaviour. The intention of the designer can get lost due to the many changes occurring to the product and the inability of the methods and tools used to capture it. Systems engineering and optimisation tools underpin industrial approaches to design, but are not without issue. The challenge is to find a route from concept to manufacture which enables designers to maintain their original intent. The novelty in this work is that the parameterisation used to build the CAD model reflects the manufacturing capability, ensuring design intent is maintained from concept to manufacture.

Combinating the process theory and system theory organically, this paper views enterprise’s technological innovation as a continuously improved system process. It builds a system model for the evaluation of technological innovation capability based on the view of process. Considering the features of cement industry, the technological innovation capabilities in cement industry are divided into innovation management capability, innovation input capability, research & development capability, manufacturing capability, marketing promotion capability and innovation output capability. And we propose a comprehensive and complete evaluation index system of cement industry’s technological innovation capability and provide a ruler for the evaluation of cement industry’s technological innovation capability

This paper illustrates a new manufacturing capability which is driven by design and sustainability. Several objectified design cases by using or waiting the new insertion of manufacturing technologies have been discussed. The cases of the leading products or systems in the world include Kazuo Kawasaki eyeglasses, Mac ibook, Boeing 787-8, integrated circuit, plasmafication, and information based medicine. The research also forecasts the value increased the activities of design centered manufacturing. After defining the scope of sustainability, an analysis of a strategy of a sustainable organization is also included. The research results predict that the competitive advantages of new products come not only from the advanced manufacturing technologies but also from a sustainable design centered manufacturing approach.

As the transferring, application and integration of knowledge can highly improve organizational dynamic manufacturing capability, this paper takes an empirical study to explore the relationships among knowledge transfer, flexible manufacturing capability and manufacturing performance based on questionnaires from 113 advanced manufacturing firms in Pearl River Delta of China by the used of structural equation model method.

Cloud manufacturing (CMfg) is a new service-oriented, highly efficient, lowly consumption knowledge based, and intelligent networked manufacturing model. It aims to achieve on-demand use, dynamic collaborative work, and circulation of manufacturing resources and manufacturing capability(MC). In order to achieve the above goal proposed, how to realize the formal description of MC is the key point in CMfg. This paper emphasizes the multi-dimensional information model of MC based on knowledge. According to the requirement and characteristics of manufacturing, the concept and connotation of MC were presented firstly in this paper, then the multi-dimension information model for MC was proposed based on knowledge, it contains three dimensions, such as elements dimension, relationship dimension, evaluation dimension.

The use of readiness levels to describe system maturity has become an increasingly recognizable element of the development of technologies for future products in the aerospace and defence sectors. Technology readiness levels (TRLs), as originally defined by NASA, are now widely used by global organizations to articulate the relative maturity of key generic technologies. The implementation of radically new manufacturing capability can also benefit from such an approach. However, the direct use of TRLs in a manufacturing environment is problematic on the basis that it is hard to interpret them precisely, and because the effectiveness of the technology itself is only one of a number of success factors associated with a successful implementation. For several years now the aerospace industry has recognized the need for a manufacturing specific readiness interpretation to enable the delivery of new capabilities in a defined sequence of events. This paper describes an approach used within a single aerospace organization, Rolls-Royce plc. The framework has been identified as a good practice by the UK Aerospace Design and Manufacturing National Technical Committee.

Cloud manufacturing (CMfg) is a new service-oriented, highly efficient, lowly consumption knowledge based, and intelligent networked manufacturing model. It aims to provide theoretical and technical supports for the transformation from production-oriented manufacturing to service-oriented manufacturing [1]. In order to further analyze the connotation and characteristics of CMfg, multi-view models for CMfg are investigated based on [1] and [2] in this paper. The first is the network view model, which describes four kinds of network involved in the running process of CMfg system; the second is the function view model, which describes the functional subsystems of CMfg; the third is the running view model, which represents the running process after a requirement is submitted to CMfg system.

Manufacturing strategy is a plan for moving a company from where it is to where it wants to be. Determining the best manufacturing strategy is not easy because of the wide range of choices and constraints a company faces. Manufacturing strategy frameworks or models are helpful because they identify the objects that comprise manufacturing strategy and organize these objects into a structure that enables a company to understand and use the objects to develop strategy. Many frameworks are possible and there is no single framework that is best for all companies. In this paper, we are interested in the levels of cost, quality, delivery, and flexibility that manufacturing provides for each product family it produces. This is determined primarily by a company's factories-within-a-factory (FWFs) and so the level of analysis in this paper is the FWF. We identify and examine five manufacturing strategy objects (production systems, manufacturing outputs, manufacturing levers, manufacturing capability, competitive analysis), linkages between these objects, and the manufacturing strategy framework for an FWF that follows from these objects and linkages. We apply the framework to the FWFs of two multi-national companies. This paper is descriptive and exploratory. Strategy objects, linkages, and framework are presented and their use is illustrated. The work of rigorous empirical analysis is left for future research.

Lonza (SWX: LONN) was founded in 1897 in Valais, Switzerland, on the banks of the Lonza River. With a long history of chemical manufacturing and custom services to the pharmaceutical and chemical industries, its expansion into the biotechnology sector was a response to the growing demand for high-quality reagents and custom manufacturing capabilities to support life science research. The acquisition of the Bioproducts and Biopharmaceuticals Companies of Cambrex in 2007 solidified Lonza’s presence in the life science market and expanded a world-class manufacturing capability to support the commercialization needs of the nascent regenerative medicine market.

In the mold parts industry, customers typically place orders for order-made parts with some changes to the design specifications of ready-made parts within the extent of the manufacturing capability of the supplier. Being customized for ready-made parts, existing e-Catalog systems cannot support this trade pattern. To solve this problem, an engineered-to-order (ETO) approach is proposed here, enabling the trade of order-made parts in an e-Catalog system by utilizing the design and manufacturing knowledge of part suppliers. After addressing technological challenges and their solutions, we describe application results of the ETO approach to two types of mold parts — ejector pins and mold bases.

Pfizer API manufacturing consists of 16 sites around the world and represents a large manufacturing capability. This network has expanded in recent years through mergers. This community of manufacturing sites represents a wide range of practical knowledge for conducting safe API (active pharmaceutical ingredient) manufacturing. Taking advantage of this wealth of experience, Pfizer manufacturing operations performed a global survey of hydrogenation current practices. From the information gathered, a “Hydrogen and Catalyst Handling Good Practice” guide was developed that covered the facility design and operational practices. The team that developed the “Good Practice” guide is also involved in overseeing the implementation of the recommended practices at all manufacturing sites conducting hydrogenations. © 2005 American Institute of Chemical Engineers Process Saf Prog, 2005

The Industrial Research Limited (IRL) ceramics research programme has activities in electroceramics, advanced refractories and engineering ceramics aimed both at the initiation and development of new manufacturing enterprises and the uptake by New Zealand industry of advanced ceramic technologies. The research team has considerable expertise and experience in sialon ceramics and composites that has underpinned the development of a new advanced refractory manufacturing capability in New Zealand. The team’s capability in engineering ceramics is based on considerable research into new forming techniques and encompasses new ceramic-metal composites. Increasingly the team is prototyping high value added, high performance ceramic bodies with industry partners. A rapidly growing capability in electroceramics has targeted the communications and electronics industry. Current research includes the prototyping of a new design broadband piezoelectric transducer, suitable for application in high definition sonar.

Manufacturing outsourcing has been regarded as a strategic approach to enhance competitiveness of manufacturing enterprises. However, making an outsourcing decision based on historical data and subjective experience in one-of-a-kind production (OKP) is deficient and unpersuasive. Meanwhile, manufacturing capability (MC), comprised of processing capability and production capacity, is the most important factor for outsourcing decision-making (ODM). In this paper, a three-phase description, match and evaluation model of MC is proposed to provide outsourcing decision-making support for manufacturing enterprises. Firstly, a description model of MC is developed based on ontology; then, a four-step match method is put forward to match the processing capability; finally, the evaluation of production capacity is carried out by dealing with the dynamic flexible job-shop problem using the nondominated sorting genetic algorithm II (NSGA-II). A simulation study is analyzed to validate the proposed model.

Manufacturing companies are increasingly dependent on outsourcing to improve their competitive position. At the same time, the approach to supplier selection has dramatically changed from being price-driven to one based on overall capability of the supplier, very much in evidence in the automobile castings sector facing the challenge of mass customization. In this study, 18 criteria have been identified for casting supplier assessment and Segregated in four groups-product development capability, manufacturing capability, quality capability, and cost and delivery. A systematic approach to evaluating casting quality suppliers has been developed using the analytical hierarchy process, which enables the combination of tangible and intangible criteria and checking the consistency of decision-making. The approach has been implemented in a prototype web-based system.

This paper describes the process integration between pre-clean and poly-silicon (poly) chemical mechanical polishing (CMP) processes that result in the most cost effective manufacturing capability. It is shown how the choice of pre-clean and dryer variables can influence the throughput of the poly CMP process. This indirectly takes away redundant process steps and reduces manufacturing cost. It was observed that different pre-clean process variables result in various surface potential charges and conditions that can influence the polish rate of the poly-silicon during the CMP process.

In this paper we examine the technical and business environment in which 193 nm photoresist R&D is conducted today. Semiconductor industry predictions of lithographic requirements for future generations of DRAM and Logic indicate the need for 0.18 and sub 0.18μm manufacturing capability within the next decade. 248nm DUV lithography and the tool/photoresist infrastructure is just reaching the state required for manufacturing at 0.25μm dimensions after a decade of intensive effort at tool and photoresist development. 193nm tool and photoresist development is beginning to demonstrate potential for 0.18-0.15μm capability but much progress is required for the 193 lithography infrastructure to reach a the point at which manufacturing capability can be applied to the 1Gb and later generations of semiconductor technologies. In this paper we will compare and contrast 248 and 193nm photoresist R&D.

The transfer of lead molecules from discovery into process development at a relatively fast pace requires a process of candidate selection that assesses if a candidate is not only active and safe but also “manufacturable.” Formulation and process stability of potential candidates help narrow down lead candidates at an early stage, prior to large-scale manufacturing, by a process of rank-ordering properties generated from process and long-term stability studies. Such an assessment of the molecules’ manufacturability is especially useful when binding affinity and bioactivity are comparable among the various candidates under question. This chapter reviews several case studies that explore the utility of early-stage molecule or manufacturability assessments in moving forward therapeutic candidate/s by finely balancing potency and pharmacokinetics with the manufacturing capability of the candidate/s under question.

With the development of information technology, many new manufacturing models, e.g. virtual manufacturing, cloud manufacturing, have emerged to enhance interoperability and collaboration among the manufacturing enterprises. As a dominate factor for production performance, manufacturing capability has attract great attention and needs to be well analyzed and measured to assist the decision making in manufacturing process. A number of works have been carried out for measuring manufacturing capability. However, most of them modeled manufacturing capability in a static manner, without considering the dynamic characteristics as well as the online and real-time collected manufacturing operation data. In this paper, we analyze the components of manufacturing capability and propose a dynamic comprehensive evaluation method of manufacturing capability for a job shop, using subjective and objective analysis. A case study is presented and the results demonstrate that it is effective and flexible to evaluate the manufacturing capability for a job shop.

Purpose The purpose of this paper is to explore the relationship of strategic manufacturing effectiveness utilizing the four-stage model of Hayes and Wheelwright (H-W) with overall performance of manufacturing, market alignment and production competence (PC). In addition, it attempts to understand the relationship of strategic manufacturing effectiveness with manufacturing capability development modes, strategic groups of companies and the nature of improvement programs being employed. Design/methodology/approach Structured questionnaire was used to capture data from manufacturing organizations. Responses from managers of 47 Indian manufacturing companies were used to test the seven propositions that were developed to examine the paradigms of manufacturing competence. Findings The analysis revealed that the strategic manufacturing effectiveness of manufacturing companies based on H-W’s four-stage model has significant positive correlation with the overall performance of manufacturing and PC of the company. Further, the analysis substantiated the relationship of strategic manufacturing effectiveness with capability development process and the nature of improvement programs. Research limitations/implications This exploratory study is based on a small sample of manufacturing companies with diversity and hence it may not be representative of all industry sectors. Second, it has used several scales for measuring the relevant constructs which themselves are not proven, hence, the findings should be taken with caution. Originality/value This is an initial research focussing on the relationships among different elements of manufacturing competence such as manufacturing capabilities, PC, manufacturing capability development mode and overall performance of manufacturing with strategic manufacturing effectiveness using H-W model. H-W model was primarily proposed as an audit tool for managers, was hitherto not adequately studied in relation to other paradigms of manufacturing competence.

In recent years, hybrid manufacturing technologies that combine different processes (e.g. additive and subtractive processes) together have gained significant attention. This is due to their ability to capitalise on the advantages of each individual process, whilst minimising their disadvantages. However, there are limited process planning methods that are able to effectively utilise manufacturing resources for hybrid processes. In this paper, a hybrid process entitled iAtractive, combining additive, subtractive and inspection processes, along with part specific process planning is proposed, aiming to provide the designer with greater manufacturing capability and flexibility. This novel process planning approach enables a plastic part to be manufactured in a proper way in terms of process capabilities, production time and material consumption. This approach can be also adopted to remanufacture and reincarnate exiting parts or legacy products into other products. In this paper, the principle and framework of this process planning approach is presented and a test part was manufactured to validate this innovative approach.

Automation of polymer composite manufacturing would allow better control of part quality and consistency, reduce cost, and improve quality of work environment. In this article, automation of the different stages of the manufacturing process, fully automated procedures, and machining of the composites is discussed. The cost and manufacturing capability limitations are the two main obstacles, which limit use of composite parts in consumer products. Expansion of automated composite manufacturing facilities would eliminate these obstacles, allowing large-scale production of high quality products. Keywords: composite; automation; machining

During the last eighteen months, Abound Solar (formerly AVA Solar) has enjoyed significant success under the SAI program. During this time, a fully automated manufacturing line has been developed, fabricated and commissioned in Longmont, Colorado. The facility is fully integrated, converting glass and semiconductor materials into complete modules beneath its roof. At capacity, a glass panel will enter the factory every 10 seconds and emerge as a completed module two hours later. This facility is currently undergoing trials in preparation for large volume production of 120 x 60 cm thin film CdTe modules. Preceding the development of the large volume manufacturing capability, Abound Solar demonstrated long duration processing with excellent materials utilization for the manufacture of high efficiency 42 cm square modules. Abound Solar prototype modules have been measured with over 9% aperture area efficiency by NREL. Abound Solar demonstrated the ability to produce modules at industry leading low costs to NREL representatives. Costing models show manufacturing costs below $1/Watt and capital equipment costs below $1.50 per watt of annual manufacturing capacity. Under this SAI program, Abound Solar supported a significant research and development program at Colorado State University. The CSU team continues to make progress on device and materials analysis. Modeling for increased device performance and the effects of processing conditions on properties of CdTe PV were investigated.

Cloud manufacturing (CMfg) is a new manufacturing paradigm proposed recently. The existing research on CMfg stays on its concept, architecture, and running model. One of the typical characters of CMflg is on demand use and pay of manufacturing capability and manufacturing. Therefore, it is essential to investigate the cost issues of manufacturing cloud service in CMfg. The cost of cloud service (CS) in CMfg is studied from three different aspects in this paper, and multi-view models of cost are proposed, they are (a)The first phase is to build the cost constitute model viewed on the whole life-cycle of CS in CMfg. The second phase is the cost constitute model from the view point of related manufacturing enterprises in which providing, composing, and invocating cloud services are provided. Finally, the cost constitute model based on the cloud manufacturing services platform is evaluated.

Many large electronic systems manufacturers have captive internal ASIC design and manufacturing capability. The ASIC environment is driven by continuous and significant advances in basic design and manufacturing technology, CAD tools, and design complexity. This paper introduces a framework for managers charged with deriving competitive advantage in this environment. The framework is made up of four parts: strategic intent, guideposts; organizational structure; and coordination arrangements. The critical issues of organizational learning and internal and external linkages between task groups are described and highlighted. Application of the framework is illustrated with the experiences of an electronic-systems manufacturer.

According to the characteristics of the equipment manufacturing industry innovation capability, innovation capability to establish the equipment manufacturing industry evaluation index system, using the 2007 National Bureau of Statistics released the seven sub-sectors of China's equipment manufacturing industry, the relevant statistical data to construct a factor analysis evaluation model, of 31 provinces, municipalities, the innovative capability of the equipment manufacturing industry to conduct a comparative analysis of various regions to obtain equipment manufacturing innovation capability comprehensive evaluation and sorting order of precedence of the situation, then the analysis results of the corresponding conclusions. Finally, according to China's equipment manufacturing capability of independent innovation and strong performance in a targeted manner proposed to increase the innovation capability of China's equipment manufacturing industry recommendations.

The United States Air Force (USAF) should not attempt to proactively manage the US aerospace industrial base for the purpose of preserving a domestic development and manufacturing capability to produce future generations of US military aircraft weapon systems. It is the mission of the USAF to fly, fight, and win in air, space, and cyberspace. It is not the mission of the USAF to sustain the US aerospace industry. Preservation of the US aerospace industry is a national policy issue that should be addressed by the president of the United States in partnership with the US Congress. They are the only entities that can appropriately balance the military needs of the Department of Defense (DoD) and the USAF against the other competing requirements within the United States.

Sorting and mating is a very common practice in high precision manufacturing, as well in the watch industry, biomedical or automotive industry. This strategy helps to increase the assembly yield, but is costly and timeconsuming. The question is, when is it necessary to apply sorting and mating, and when can it by avoided without loss in product quality? We furthermore show in this paper that the measurement precision is often lower than that of manufacturing. New and more precise manufacturing equipment and assembly devices allow for narrower distributions, and this raises many questions: is it possible to stop sorting? how can we be sure of the quality of the components and of the products? A case study at the company MPS AG, manufacturer of miniature ball bearings, illustrates this trend. We propose another manufacturing and assembly strategies, and show what the conditions are that are necessary to permit this approach.

This paper describes design of a low cost, ultrasound gel from local products applying aspects of Human Centered Design methodology. A multidisciplinary team worked with clinicians who use ultrasound where commercial gel is cost prohibitive and scarce. The team followed the format outlined in the Ideo Took Kit. Research began by defining the challenge "how to create locally available alternative ultrasound gel for a low-resourced environment? The "End-Users," were identified as clinicians who use ultrasound in Democratic Republic of the Congo and Ethiopia. An expert group was identified and queried for possible alternatives to commercial gel. Responses included shampoo, oils, water and cornstarch. Cornstarch, while a reasonable solution, was either not available or too expensive. We then sought deeper knowledge of locally sources materials from local experts, market vendors, to develop a similar product. Suggested solutions gleaned from these interviews were collected and used to create ultrasound gel accounting for cost, image quality, manufacturing capability. Initial prototypes used cassava root flour from Great Lakes Region (DRC, Rwanda, Uganda, Tanzania) and West Africa, and bula from Ethiopia. Prototypes were tested in the field and resulting images evaluated by our user group. A final prototype was then selected. Cassava and bula at a 32 part water, 8 part flour and 4 part salt, heated, mixed then cooled was the product design of choice.

General-purpose elastomers played a critical role in the history of the last half of the 20th century. In 1942 the Rubber Reserve program developed both the basic technology and manufacturing capability to make emulsion styrene butadiene rubber (SBR) just a few years after World War II had interrupted natural rubber supplies. Historians have noted that the scientific contribution to that effort is comparable to the nuclear research program at Los Alamos that occurred at the same time (1). After the petroleum shortages of the 1970s, fuel economy became a primary driving force in the automotive industry, and the tire industry was challenged to develop new products that would improve gas mileage. New elastomers based on solution SBR technology proved to be part of the answer.

In order to achieve world-class competitive manufacturing capability, the concept of supplier partnerships was developed, with a win-win approach. Total equipment performance, which included process and manufacturing capability, strong vendor relationships, vendor contract maintenance, training, field service support, and continuous improvement methodology, was emphasized. An off-site, nonproduction facility was set up to help develop manufacturable solutions. The equipment set was exercised in the facility to simulate a volume production environment. The purpose of the exercise was to prove that the equipment can meet the intended need. Process and hardware capability of the equipment set was evaluated and documented over a large wafer volume. The result of this methodology was qualified production at high volume. >

Microvia technology can allow lower manufacturing cost while offering higher interconnect density. Critical hurdles in actually achieving lower cost depend on design and manufacturing capability. With regard to designs, the degree to which PWB designers take advantage of microvia technology directly translates into cost savings particularly if area reduction can be maximized. Manufacturing capability also impacts the likelihood of cost reduction. Specifically, how panel size is traded off with manufacturing yield has great influence on board cost. This article shows a design case study to show how the tradeoff can be made.

Knowing how well a manufacturing process will fit a new location prior to its transfer is a necessary, but not sufficient, condition for predicting transfer problems. This paper argues that firms must also consider how easy a manufacturing process is to transfer. A pre-transfer tool, tested here in multiple case studies, uses the dimensions of location fit and ease of transfer to provide a means of measuring the fitness for transfer of a firm's manufacturing processes.

While no-clean technologies do reduce adverse environmental impact, their effect on product reliability must be considered. Manufacturers who choose to convert to no-clean materials and processes need assurance that product performance is not adversely affected. Environmental effect, manufacturing capability, and product reliability are all valid criteria for a materials and process selection method.

Entering the era of deep sub-micron, Singapore has put a lot of effort into the development of design and manufacturing capability in the microelectronics industry. The Institute of High Performance Computing has invested in manpower, high-performance computing hardware, and state-of-the-art EDA CAD tools to assist and support local microelectronics industry in applications such as 3D parameter extraction and hard IP migration.