Dimitrios E. Koulouriotis

Towards a holistic knowledge management model

Knowledge management (KM) has been gradually established as a strong methodology to support business viability, competitiveness and growth; however, the lack of maturity is obvious, as evidenced by divergent points of view in critical sub‐domains of the related theory and practice, such as the spectrum of processes and the clusters of tactics scheduled to underpin them. The systems thinking logic, the discipline for seeing structures underlying complex phenomena, is perceived as a promising direction for consolidating the various approaches and developing a holistic KM paradigm. Through the integration of the fragmented landscape of knowledge management on a transparent and concrete framework based on cause‐effect relationships, not only the underlying theoretical assumptions are clarified and subjected to further analysis at a strategic level, but also practical issues concerning planning and decision making become less complicated, increasing effectiveness.

A Unified Methodology for Computing Accurate Quaternion Color Moments and Moment Invariants

In this paper, a general framework for computing accurate quaternion color moments and their corresponding invariants is proposed. The proposed unified scheme arose by studying the characteristics of different orthogonal polynomials. These polynomials are used as kernels in order to form moments, the invariants of which can easily be derived. The resulted scheme permits the usage of any polynomial-like kernel in a unified and consistent way. The resulted moments and moment invariants demonstrate robustness to noisy conditions and high discriminative power. Additionally, in the case of continuous moments, accurate computations take place to avoid approximation errors. Based on this general methodology, the quaternion Tchebichef, Krawtchouk, Dual Hahn, Legendre, orthogonal Fourier-Mellin, pseudo Zernike and Zernike color moments, and their corresponding invariants are introduced. A selected paradigm presents the reconstruction capability of each moment family, whereas proper classification scenarios evaluate the performance of color moment invariants.

Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms

Several efficient pull production control policies for serial lines implementing the lean/JIT manufacturing philosophy can be found in the production management literature. A recent development that is less well-studied than the serial line case is the application of pull-type policies to assembly systems where manufacturing operations take place both sequentially and in parallel. Systems of this type contain assembly stations where two or more parts from lower hierarchical manufacturing stations merge in order to produce a single part of the subsequent stage. In this paper we extend the application of the Base Stock, Kanban, CONWIP, CONWIP/Kanban Hybrid and Extended Kanban production control policies to assembly systems that produce final products of a single type. Discrete-event simulation is utilised in order to evaluate the performance of serial lines and assembly systems. It is essential to determine the best control parameters for each policy when operating in the same environment. The approach that we propose and probe for the problem of control parameter selection is that of a genetic algorithm with resampling, a technique used for the optimisation of stochastic objective functions. Finally, we report our findings from numerical experiments conducted for two serial line simulation scenarios and two assembly system simulation scenarios.

A theoretical study of the relation between TQM, assessment and sustainable business excellence

This work aims to create a map for academics, researchers, and those interested in business excellence. In the first place, the authors make a reference to the evolving path of business excellence and its relations with total quality management (TQM). Subsequently, the study examines the soft factors of TQM and their role in sustainability. A properly designed assessment procedure supported by an information system outlines the situation of the organisation and can help it to be improved. The authors propose a conceptual framework for performance assessment. To win a business excellence award, great amounts of effort, money, time, and personnel are required. Adopting a business excellence framework is a task that requires commitment, communication, and co-operation. A clear vision, an appropriate culture and willingness to change can facilitate the implementation of such a framework. Nowadays, crises affect many organisations around the world. In such a situation, change is a crucial factor for survival and success. However, change in a turbulent environment cannot be managed only by the traditional approaches to excellence, because they are mostly valid when the environment is stable. In view of this fact, a framework for sustainable business excellence is proposed here.

A fuzzy multi-sensor architecture for indoor navigation

This paper presents an indoor navigation system based on sensor data from first responder wearable modules. The proposed system integrates data from an inertial sensor, a digital camera and a radio frequency identification device using a sophisticated fuzzy algorithm. To improve the navigation accuracy, different types of first responder activities and operational conditions were examined and classified according to extracted qualitative attributes. The vertical acceleration data, which indicates the periodic vibration during gait cycle, is used to evaluate the accuracy of the inertial based navigation subsystem. The amount of strong feature correspondences assess the quality of the three-dimensional scene knowledge from digital camera feedback. Finally, the qualitative attribute, in order to evaluate the efficiency of the radio frequency identification subsystem, is the degree of probability of each location estimate. Fuzzy if-then rules are then applied to these three attributes in order to carry out the fusion task. Simulation results based on the proposed architecture have shown better navigation effectiveness and lower positioning error compared with the used stand alone navigation systems.

A multicriteria model on calculating the Sustainable Business Excellence Index of a firm with fuzzy AHP and TOPSIS

Purpose – The purpose of this paper is to provide an integrated methodology for benchmarking the sustainability of organizations. The fuzzy analytical hierarchy process (FAHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods have been used for this purpose. The FAHP is used to determine the weights of the criteria by decision makers, and the rankings of the alternatives are determined by TOPSIS. The proposed instrument is used to calculate the Sustainable Business Excellence Index (SBEI) and its potential impact on the formulation of firm strategy. To demonstrate the applicability of the model, illustrative examples are presented. Design/methodology/approach – After a careful literature review, a sustainable business excellence framework is created and a fuzzy system is developed to assess firms’ sustainability. Finally, the SBEI is computed. Findings – The results indicate that the suggested fuzzy approach is feasible for benchmarking the sustainability of organizati...

An intelligent multi-sensor system for first responder indoor navigation

This paper presents an indoor navigation system based on sensor data from first responder wearable modules. The system combines an inertial measurement unit, a digital camera and a radio frequency identification device in a way that allows the advantages of each sensor to be fully exploited. The key to this synergy is the extracted qualitative criteria which characterize the performance of each sensor subsystem at various first responder activities and operational conditions under certain time intervals. The accuracy of the detected walking pattern through measurements of the acceleration magnitude from the inertial sensor is utilized for the performance evaluation of the dead-reckoning algorithm. The amount of correct feature matches is linked to the three-dimensional scene representation from the camera navigation subsystem and finally, the degree of probability of each radio frequency identification location estimate is exploited as a straightforward qualitative criterion. The final fused location estimation is extracted after applying fuzzy if–then rules at each time interval. Since the inertial sensor suffers from accumulated drift, the rules of the fuzzy inference system drop the measurements from the inertial measurement unit whenever the other two subsystems perform adequately. Extensive comparison and experimental results based on the proposed architecture have shown not only better navigation effectiveness and lower positioning error compared with other first responder navigation systems but also increased accuracy in various and challenging operational conditions.

Health products sales forecasting using computational intelligence and adaptive neuro fuzzy inference systems

In our days the importance of reducing the inventory level in a healthcare organization is increasing fast. As a result, the value of an accurate supply forecast is becoming more relevant. The main objective of this paper is to analyze and compare some of the most popular and widely applied techniques available based on computational intelligence. In addition, it aims to demonstrate the competitiveness of the aforementioned using real-world data. The methods that are employed include neural networks (feed forward, radial basis, generalized regression, and recurrent networks) and the hybrid neural fuzzy system (ANFIS). The experimental part of this study is conducted with the use of sales’ data extracted from the database of a major Greek medical supplier. A two-year period was employed in order to gather the appropriate sales figures about some of the most popular medicines and subsequently each technique’s forecasting ability was tested against a third year. The parameters of each technique are then fine-tuned in order to minimize the performance functions. Finally, a brief statistical analysis of the techniques used is performed to facilitate the comparison between them and define the most appropriate method for this particular issue.

Nonlinear cause-effect relationships in Fuzzy Cognitive Maps

Fuzzy Cognitive Maps (FCMs) have been widely used for a plethora of applications, exploiting its ability to represent the knowledge and the dynamics of a system. The diversity of inference mechanisms, which have been proposed until nowadays, discloses the effort for an effective concept value calculation methodology. In contrast with the most research efforts which consider a linear relation of the influence that a concept exercise to another concept, in this paper a nonlinear representation of that influence is introduced. The importance which is associated with the proposed methodology is that a nonlinear cause-effect relationship strengthens the behavior of an FCM through the simulation process. The analysis of this proposal through a progressive reasoning is followed by appropriately selected problems.

A preliminary estimation of analysis methods of vibration signals at fault diagnosis in ball bearings

In this paper, a preliminary estimation of the most common analysis methods of the vibration signals of a ball bearing is tried. The tested methods are the typical statistic analysis method, the Fourier transform, the frequencies spectrum analysis and the wavelet method. With the statistical signal analysis, the quantitatively differentiation (but not qualitatively) of the measured signals in the level of vibration is easily detected, which is potentially owed in some fault bearings. With the Fourier transform detected, the frequencies of damage are presented during the vibration of a bearing. The use of spectral of frequencies of signals as well as energy that is contained in them assists to detect and/or confirm the frequencies that were already detected with the Fourier transformation. The analysis with use of continuous transformation with wavelets seems to be more promising than the discrete one, but a further experimentation is needed with various loading conditions and other type of bearings before a safe result is concluded.