The recent advances in Smart Manufacturing open opportunities in Maintenance and Management of its assets through new support strategies. This trend allows the collection of machine operation data in the shop floor, in order to interact with cyberspace computers through a communication network, therefore enabling the Cyber Physical System concept (CPS). Furthermore, the rapid advances of Information and Communications Technology (ICT) provide means to analyze Big Data, more quickly, autonomously, ubiquitously and in real time, offering information that assist in more efficient decision making in manufacturing processes. Nowadays, Prognostic and Health Management (PHM) leverages researches in the new generation of manufacturing. For this, an architecture called 5Cs, that directs the PHM implementation in CPS context is being adopted with expressive results, which allows the application of several math and/or Artificial Intelligence techniques to estimate the assets' remaining useful life. In particular, the use of Experts Systems and semantic information modeling can make it possible to represent knowledge found in the scientific literature and consolidated standards about the subject. This paper uses methodology of ontology development 101, which guides management, development and documenting of a formal taxonomy of failure prognostics. For model creation and evaluation, the Protégé suite is used, for it allows future researches to interact with the model, such as monitoring techniques and failure diagnostics in order to simulate real cases of mechanical components. This way, new possibilities for cyberspace oriented application development for industrial machine health management are revealed.
Product development projects present numerous uncertainties that lead to risks, especially in the design phase of the product which involves qualitative, abstract and insufficient information about the problem and the product that is the object of development. Risk management in product design consists of a formal and systematic management process which aims to identify, analyze, treat, monitor and control risks related to their activities and tools. Expert system is an artificial intelligence based system that simulates the judgment and behavior of a human with expert knowledge and experience in a particular field. It contains a knowledge base system with accumulated experience and a set of rules. This article aims to provide guidelines for the development of an expert system for the risk identification phase in product design. It also approaches a risk management methodology with focus on the risk identification that has been already developed and assisted to product design. This paper concludes with a partial and general conceptual vision of the expert system to be developed.
This study aims to evidence problematic aspects for the implantation of FMEA method (Failure Mode and Effects Analysis) in the Products Development Process (PDP) of industries. The technical procedures used were literature review and action research, besides the implantation of FMEA method in a big company of metal-mechanic industry. The research offers a synthesis of various experiences about the implantation of design methods in the industry, rescuing values of human wisdom that previously had not received great attention. The main result of this research is an implantation process of FMEA method, consisting of main stages, results and recommendations to help companies to use the methods for technological innovation and increase the competitiveness.
The identification of value creation in organizations is a complex process that involves internal and external factors to them. When applied to Big Data environments, this process becomes even more challenging because it takes also into account, from predictive analytics, the uncertainty about future processes of value creation. Big Data environments operate in a scale of large volumes of parallel-processed data; and aim to generate relevant information that otherwise would be impossible for traditional systems, especially if we expect a good performance of transaction speed and of coping with the extensive variety of data types, inherent to such environments. This paper aims to characterize the creation of value in organizations that implement Big Data. In order to fulfill this purpose, we undertook a theoretical study, which relied in a qualitative method approach of bibliographical, exploratory and descriptive nature. Finally, since this work is still on progress and it is not yet a conclusive proposal, we aim to compare our preliminary results to the typical perception of value creation, found in the literature. We also propose a discussion about the characterization of value creation in Big Data environments, to be taken further.
Advances in technology have promoted offshore wind energy being one of the most promising renewable energy sources. Offshore wind farms are usually positioned in an opened space far away from the seashore where the wind is strong enough to generate electricity effectively and reliably. However, due to location characteristic hard–to–reach, the operation and maintenance cost of the offshore wind farms are high and the economic evaluation is uncertain. A huge number of researches about offshore wind energy have emerged recently in response to these issues. However, the researches considering the effects of various influential parameters to access the reliability of offshore wind turbine remain small and still limited, especially the parameters related to the dynamic weather conditions such as real-time utilization under typhoon and flood impacts. This paper proposes an approach to analyze the life–cycle–cost of the offshore wind turbines under maintenance scenarios and environmental influences, with the support of probabilities distribution method. The electricity generated by the offshore wind turbine is calculated based on the real weather conditions collected in a variety of locations throughout Taiwan such that the proposed life–cycle–cost model is more reliable and accurate than the conventional approaches. The results show that Typhoon and Maintenance cost occur 4.2% and 19.6% respectively. Moreover, offshore wind energy is an excellent environmental solution with high economic benefit on sites where the wind resource is abundant.
The need for continuous technical development brings fresh innovatory solutions and at the same time indicates new trends. For years, common applied solutions have not been adequate enough to the newly established and evolving needs. Furthermore, the global development brings new challenges and needs for the aviation propulsions. An example of such a problem can be particularly noticeable in recent years, with the growing popularity of remotely controlled, small flying objects, commonly called drones, which designated new opportunities in the field of aviation, as well as become a source of new needs. An unusual challenge is the application of a drone in extremely difficult weather conditions or surrounding conditions causing its multiple and relatively strong bounce off the obstacles that may occur while using the drone to inspect ventilation ducts, in confined areas with a large number of installations, in dense forest conditions or in space with strong turbulent atmospheric conditions. In such cases it is not possible to avoid multiple collisions with various obstacles. It is necessary to design drone and its drive so that such collisions will not damage the flying object and moreover that maintenance of the full control of the drone will be possible. As the answer to those needs a drone was designed with a passive protection system. To protect against the collision consequences, the static parts of the drone—the power supply, controllers, motors and extension devices as well as the rotating parts—propellers are covered outwardly with a protection shield. In this paper the behaviour of the protection system of flying autonomous robot's propulsion during collision with perfectly rigid obstacle was checked. The performed numerical crash analysis simulates probable collision situations in operating conditions specific for the researched drone.
The aero-engine industry is continuously faced with new challenging cost and environmental requirements. This forces company's, active in the industry, to work toward more fuel efficient engines with less environmental impact at a lower cost. This paper presents a method for assessing producibility of large sets of components within aircraft engines to enable a Set-Based Concurrent Engineering development approach. A prototype system has been developed aimed at enabling weldability analysis at a sub-supplier within the aero-engine industry. It is a part of a multi-objective decision support tool used in early design stages. The tool produces sets of CAD-models reaching the hundreds for different analyses, mainly focusing on performance aspects within structural analysis, aerodynamics and thermodynamics.
The continuous improvement of products to attend consumer needs are increasing the product development process's (PDP) complexity. This demands that systems offer support to many different stages of PDP, as much as in tangible products (physical objects) as in intangible products (services, software). Concurrently, it was identified a considerable increase in the quantity and level of detailing of the information from those systems. However, there was also an increase in the number of semantical obstacles on sharing the latter. These semantical obstacles are mainly related to the heterogenic nature of the information, which has its captured meaning interpreted in a divergent way, increasing the project costs and development time. In this context, along with the Interoperable Product Design Manufacture System (IPDMS) concept, this article proposes the development of the core ontologies from the foundation view of this new methodology, in order to aid the semantical interoperability in the Product Design stage, further improving the exchange of information during different phases of the PDP. The first stage of this research is dedicated to review the main concepts on PDP, interoperability and ontology engineering. The second stage is dedicated to the concept exploration on the creation of core ontologies and its relation to the foundation view of the IPDMS.The final stage regards the creation of the core ontologies, which will serve as basis for further development of the system and work as knowledge basis for the entire concept. This will allow an analysis on consistency and information sharing with other elements of the Product Design and Manufacture in future stages. The creation of the core ontologies was related to the development of a plastic injected product, gathering domains such as Design and Materials, that will further combine to create the product model ontology. The development of the concept can bring advantages to the PDP and increase the automation during the decision making process. This tool of support showed potential to aid the exchange of information and inconsistency analysis at the product development process in the future, allowing risks reduction and rework at advanced project stages, also remarkably reducing time and total project costs.
The procedure for obtaining the particle size distribution by visual inspection of a sample involves stereological errors, given the cut of the sample. A cut particle, supposedly spherical, with radius R, will be counted as a circular particle with radius r, r≤R. The difference between r and R depends on how far from the center of the sphere the cut was performed. This introduces errors when the extrapolation of the properties from two to three dimensions during the analysis of a sample. The usual method is to correct the distribution by probabilistic functions, which have large errors. This paper presents a method to reduce the error inherent to this problem. The method is to compute a simulation of the preparation process in a sample whose structure can be described by non-penetrating spheres of various diameters which meet a known probability distribution function, for example, a log-logistic function, or even a constant function. For each distribution radius, a number of spheres is generated and virtually cut, generating a bi-dimensional (2D) distribution. The 2D curves of the spheres distribution obtained in this simulation are compared with that obtained by the experimental procedure and then the parameters of the threedimensional distribution function are adjusted until the 2D curves are similar to the experimental one using the optimization method Simulated Annealing for the curve-fitting. In future this method will be applied to the analysis of the oil reservoir rocks.
This paper presents a transdisciplinary research of an electromechanical quartz crystal resonator (QCR) with consideration of surface elasticity effect of nanowires (NWs) loading arrays, which crosses boundaries of mechanics and electricity, and links macro and nano technologies. The governing equations of NWs are derived from the Timoshenko beam theory in consideration of shear deformation. The electrical admittance is described directly in terms of the physical properties of the surface NWs from an electrically forced vibration analysis. The results will be helpful to the design of nanosized beams loaded acoustic wave sensors and some related applications.
The large amount of available design information from different areas has become common in most organizations. Under these conditions, there are difficulties in sharing and reusing knowledge, especially by the fact that this knowledge is available within the company in different formats and locations. Due to this, design engineers often fail to use such information. To ensure a better use, it is important to organize and integrate the available knowledge in a collaborative manner. In this context, the Knowledge-based Engineering (KBE) approach can be associated. Through KBE concepts, the current study aims to develop a set of tools for assisting decision making, by storing and providing useful information in a timely manner. Such solution should meet the needs of its users (i.e. designers), as well as improve the quality of design activities along the Product Development Process (PDP). For this study, still under development, the following steps have been adopted: (a) delimitation of action scope (i.e. steps of PDP to be focused); (b) knowledge capture; (c) knowledge structuring through ontologies; (d) standardization; (e) development of rules; (f) creation of application solutions; and (g) performance evaluation of solutions. The application of the present proposal is expected to facilitate the access to information, significantly reduce the number of Engineering Change Requests (ECR's), as well as allow acquired knowledge to be used in subsequent projects (e.g. lessons learned).
Fast and dynamic development of engineering and technology forces designers to reduce time which is needed to design new technical object. The result of this process was fast development of Computer Aided Design (CAD) methods and with the development of such systems new knowledge focused on design methods based on Knowledge-based Engineering (KBE) were developed. One of KBE approaches connected with the application of CAD systems is Generative Modeling, which automates routine design performed in CAD systems. As a result design features, whole parts and even whole assemblies can be generated automatically in CAD system. These generated assemblies and elements can adapt to changed input data. Thus, Generative Modeling method can increase the speed and quality of designed elements. As a use case for application of generative modeling subassemblies of ultra-efficient electric vehicle and drive transmission assembly were used. The process of constructing generative models of assemblies and systems of ultra-efficient car was described, especially acquisition of knowledge and creating knowledge model up to integration knowledge with CAD system – in this case it is CATIA V5. The problems faced during the process of processing knowledge and solutions to these problems were addressed. Additionally, further steps for development of the models and the advantages of generative modeling approach were described.
The dimensional variations inherent in a manufacturing process are the reason for the existence of the acceptance tolerance concept on a product characteristic. The geometric quotation system has many advantages over the Cartesian system by avoiding ambiguity in the interpretation on form, orientation and location errors. The two main standards that define the geometric quotation on a mechanical design are ISO1101/2012 and ASME Y14.5-2009. However there are differences in interpretation even when the same symbols are mentioned by these standards. It is, therefore, important to know these differences to ensure the quality for companies that provide products to customers who apply different standards of geometric control. This article presents the results of perpendicularity control using each standard and their difference as an example of the impact when choosing one of them. In addition, the article shows preliminary results of a still on-going survey indicating that these differences between the standards are still little known among professionals in the areas involved in Brazil.
Healthcare processes are complex and require a high-level of interdisciplinary cooperation among the different specialists and sectors involved in their delivery. Information flows among organizational entities, sectors, areas and employees represent possible low process interoperability risks as well as noncompliance risks between business rules and actual process deliveries. Besides this complexity, the Brazilian healthcare area has a notorious problem in its public and private health care systems. These problems are of structural, organizational and financial natures, reflecting the low value attributed to quality and to the actual services in recent surveys of Instituto Data Folha and the Brazilian Ministry of Health (Ministério da Saúde). This paper intends to propose an adaptation of Process Mining as an ancillary tool in knowledge discovery processes in healthcare in order to contribute to further improving this area in Brazil. In order to accomplish this, a case study was carried out in the Erasto Gaertner Hospital, located in Curitiba – PR, Brazil, a local reference in cancer treatments.
The advancement of corporate systems and accelerated production data and information using different technologies bring the challenge to managers: the problem of how to integrate and relate the content generated by turning it into knowledge. Alternatives to this are the storage, retrieval systems and organizational content management, leaving the challenge of interoperability and standardized structure of the relationship between the document and its contents and content between different documents. In this context this article presents the proposal of an ontology, conceptual representation for information retrieval in bibliographic resources called OntoIRBR (Ontology for Information Retrieval in Bibliographic Resources). This ontology has structural elements and document management integrators associated with content management in order to enable the classification of information associated with the classification of document types and metadata.
In this work, a product conceptualization strategy based on crowd-innovation is proposed consisting of two sub-systems: crowdsourcing concept generation and collection sub-system (CCGC), and concept screening and evaluation sub-system (CSE). Specifically, a crowdsourcing development approach based on neuro-fuzzy network is established in CCGC with careful considerations regarding target analysis and task allocation. An improved concept evaluation and selection approach based on domain ontology and fuzzy clustering is established in CSE for dealing with crowdsourcing results more efficiently. To illustrate the proposed strategy, a cased study of future PC design was presented.
Academic spin-offs usually develop products and services that can be applied for different markets. This peculiarity makes it difficult to carry out marketing research, considering the diversity of segments, channels and segments to be prioritized. This article describes the problem based on the experience of an academic and medical device industry spin-off. Applying an observer-participant research method, the paper describes the development of a marketing research plan for this case and the team´s solutions for the problem. Finally, the paper identifies practices that should be investigated to improve the interface between marketing, technology management and product development.
This paper presents the results from a research project conducted by the research group Computer Supported Engineering Design (CSED) in Jonkoping University in Sweden. The project has the aim of increasing companies' ability to respond to fluctuating requirements when developing new products and product variants. The companies participating in the project represents automotive, aerospace and production equipment industries. Three different cases of applications have been developed and implemented in the companies. Product models ranging from product to knowledge centered for use in the company's product and technology platforms have been demonstrated and evaluated though interviews with professionals at the companies. To summarize, the results shows that the companies' abilities to respond to fluctuating requirements have increased albeit concerns have been raised on the maintenance of knowledge in the implementations.
The Product Development Process (PDP) multidisciplinary aspect, under Concurrent Engineering (CE) principles, leads to overwhelming complexity, where several systems, methods and tools are used in a process with intensive information flow. Nonetheless, the absence of a common language for describing information components, regarding product, process, design and business, give rise to multiple interpretations, hindering full understanding and therefore produces rework and quality issues. This scenario highlights the need for ways to make the availability of product requirement information more dynamic and scope-sensitive (i.e. different levels of abstraction) along the PDP stages. In this context, Model-based System Engineering (MbSE) and supporting system-modeling languages such as SysML propose a product representation structure, through a unique and timeless model, which potentially drives the whole product lifecycle, as the single and ubiquitous information source to stakeholders. In this sense, the goal of this work is to propose a system model that provides reliable product representation, able to support product requirement definition tasks and their use along the PDP, allowing significant gains in productivity and reduction of non-conformities. The methodology adopted in this work follows the principles of DSR (Design Science Research), considering a real scenario inserted in a multinational enterprise context, in the agriculture-applied machinery sector. The model proposed is expected to assist the generation and usage of product information at various abstraction levels, by all stakeholders during the PDP, therefore reducing rework and enhancing design quality.
Satisfying customer's emotional preferences is the key to success in the new product design and development. In this regard, the semantic differential scale is a very efficient way to collect and analyse customer's subjective impression. It helps customers to express their attitudes through a list of words such as excited and enjoyment. This method, however, could be improved by a few fresh perspectives. Firstly, the semantic items often came from an ad-hoc project, and might not be appropriate because of individual differences. Secondly, it was assumed that customers seeing a product image can recall their feelings while human emotions are evoked by multi-sensory perceptions in a real life scenario. Some words, comfortable for instance, might be only triggered when you have the physical contact with the product. Designers named it as the actual product quality, the actual experience in a human-product interaction. This work therefore aims at investigating the elicitation technique to handle the nature of user experience, such as multimodality and expression preferences. Forty female road cyclists have provided their attitudes of positive emotions towards cycling following by an actual product quality evaluation of two bicycle saddles. The results showed the effect of personal involvement on a semantic differential scale and how users perceived certain Kansei words under different interactions, viz., vision, touch and cycling. Finally, the proposed elicitation technique could help manufacturers to build the design requirement based on customer's emotional preferences before pushing it into the target market.