At the present moment, global competition between companies is leading to a constant battle for an adequate market share and this is mostly not only achieved by reducing prices but rather more ...effectively by constantly introducing new innovations at all levels and across all functions in a company. Conceptions or ideas for new products derive either from external sources (customers or buyers, suppliers, competitors, patent documentation, research centres and educational institutions, chambers, associations and institutes, fairs and exhibitions etc.) or internal sources (managers, sales representatives, merchants and commercial travellers, associate professionals and technologists, designers, in-house innovators etc.) 10. Companies in the technical field mostly acquire knowledge on the basis of researching a special group of buyers known as the “leading users”. These are the buyers who are the most advanced in terms of using a company's products and in comparison with others they identify possible improvements to products earlier. Companies use surveys, projective methods, group interviews as well as written customers’ suggestions and complaints to identify the needs and wishes of their customers. However, it has to be said that many of the best ideas evolve from the problems customers have with existing products 7.
The very core of VA is the effort to determine and eliminate those characteristics of products or services with no real value for the customer or the product, but which, nevertheless, cause costs in the production process or service delivery. Therefore, the VA process ensures a better product or service for the customer at minimal costs compared to replacing the existing product with a less favourable alternative.
In the present article, the development of a new product is outlined in which the usefulness of two methods of innovative management – VA and conjoint analysis – was shown.
The theory of production functions plays an important role in the field of economic analysis. The purpose of the current work is to investigate quasi-product production functions in microeconomics ...from the view of extrinsic invariants. Focussing on the geometric invariants of the corresponding quasi-product production surfaces, by solving some certain interesting differential equations we classify two-inputs quasi-product production functions whose production surfaces admit constant mean curvature property. Furthermore, a series of classification results and some interesting examples of quasi-product production functions are obtained, which could be applied to the study of economic analysis.
Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize ...this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.
The global demand for seafood products increased in a dynamic environment. Still, fails to achieve competitive positioning due to labeling, unattractive and unprofitable targeted segments, and less ...preferred quality and features. Thus, this study tried to create competitive positioning through features, functions, and benefits of seafood product attributes. The results arranged through consumer characteristics, consumer preference with conjoint analysis, market identification and competition with regression analysis, Multidimensional Scaling, and Correspondence Analysis from 206 respondents. The results prove that (i) canned fish, dried fish, and salted fish competed on freshness, durability, and food safety (labels); (ii) shredded fish, surimi, and pedak competed on density, taste, physiological function, and easy-to-use feature; (iii) crackers competed on taste, social function, and psychological function; (iv) shrimp paste competed on shape, color, surface condition, texture, additive content, and chemicals. The implications of the results: (i) transported and packed to processing plants and food storage facilities; (ii) an increase in food diversity, food fortification, and supplementation; (iii) cultural congruence between the product and the market with certain packaging designs, launch timing, and advertising; (iv) several methods of process, such as quick freezing and cook-chilling, pasteurized before packed or retort pouch and natural food additives.
Local mean decomposition (LMD) is a novel self-adaptive time–frequency analysis method, which is particularly suitable for the processing of multi-component amplitude-modulated and ...frequency-modulated (AM–FM) signals. By using LMD, any complicated signal can be decomposed into a number of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated signal from which physically meaningful instantaneous frequencies can be obtained. In fact, each PF is just a mono-component AM–FM signal. Therefore, the procedure of LMD may be regarded as the process of demodulation. While fault occurs in gear or roller bearing, the vibration signals picked up would exactly display AM–FM characteristics. So it is possible to diagnose gear and roller bearing fault by LMD. Targeting the modulation features of the gear or roller bearing fault vibration signal, a rotating machinery fault diagnosis method based on LMD is proposed. In this paper, firstly the LMD method is introduced; secondly, the LMD method is compared with another competing time–frequency analysis approach, namely, empirical mode decomposition (EMD) method and the results show the superiority of the LMD method; finally, the LMD method is applied to the gear and roller bearing fault diagnosis. The analysis results from the practical gearbox vibration signal demonstrate that the diagnosis approach based on LMD could identify gear and roller bearing work condition accurately and effectively.
This paper proposes a novel approach to inverse interpolating black‐box models, referred to as the cyclical inverse interpolation method (CIIM). The approach relies on the use of a multivariate ...surrogate function, expressed as a tensor product (TP) model, to systematically generate candidate inputs to the given black‐box model with the goal of obtaining interpolated outputs. While the proposed approach is largely agnostic as to the form of this surrogate function, some of its properties, such as the semantics of its input dimensions with respect to the black box model, are constructively defined. The paper demonstrates the viability of the proposed approach both from a theoretical perspective and through numerical examples. Based on these results, it is argued that the approach can be used for the exploratory identification of black‐box models that have scalar‐valued outputs and can be particularly useful in working with black‐box models that have a large number of inputs and exhibit highly nonlinear behavior.
The study demonstrates the use of a hybrid method for condition monitoring of rotary machines. The multi-scale fluctuation based dispersion entropy (MFDE) is hybrid with a local mean decomposition ...(LMD) to analysis the bearing faults. The acquired bearing signals are decomposed using LMD. MFDE values of decomposed signals are computed and are used as feature vectors in the present study. Support vector machine (SVM) is used as machine learning tool for classifying the different levels of fault severity. This study shows that, the proposed hybrid method has potential for gaining further insights into the dynamics of rotary machines.
The value of use is a specific notion but of a great generality that makes the product be regarded as a complex system that transforms itself in time, thus undergoing evolution. Therefore, the ...product is important not in itself, but for the sake of the requirements it satisfies and for the functions it provides. In the analysis of value there are connections of a technical nature that implicitly lead to connections of an economic nature. Thus, the method of the ”analysis of value” will actually examine the cost of product functions, the aim of the method being the balance of functions costs on the basis of their importance for the product. Identifying the functions represents one of the important stages of the analysis of value. The difficulty in fixing the functions derives from the fact that there are not any rules clear enough for this activity, but only principles
The first part of the article contains integral expressions for products of two Bessel functions of the first kind having either different integer orders or different arguments. A similar question ...for a product of modified Bessel functions of the first kind is solved next, when the input functions are of different integer orders and have different arguments.
Quality of a product is a function of many variables. These have been identified, and modeled in terms of quality digraph. The nodes in the digraph represent the quality features and the edges ...represent the degree of influence among these. An equivalent matrix representation of the digraph is developed to define the product system quality function (PSQF). Quality index (QI) is defined as a ratio of the actual to the ideal values of PSQF. The designer may use this index to evaluate and compare alternative designs and choose the best among these from the perspective of quality. A high value of QI indicates that the product structure is closer to the ideal state. The presented model is illustrated with an example.
PDF
