Zsolt Kemény

Survey paper: A survey of applications and requirements of unique identification systems and RFID techniques

The paper contains an overview of unique identification issues and of the various radio frequency identification techniques that are available now or will become available in the short term. The paper also compares RFID with traditional ID technologies. It shows application possibilities and gives examples of current implementations. Each application has its own requirements that translate into specific RFID-techniques, -options and -parameters. Techniques include frequency range, tag energy supply and tag writing capabilities. The data to be stored in the tag and transferred to the reader must be selected as one of the options. Parameters influence reliability and confidentiality, among other things. Information interchange issues of identifier-based operations in supply-chains are discussed as well, while the last part of the paper presents a framework for choosing an auto-ID technique in a supply chain.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

AI techniques in modelling, assignment, problem solving and optimization

This paper recapitulates the results of a long research on a family of artificial intelligence (AI) methods-relying on, e.g., artificial neural networks and search techniques-for handling systems with high complexity, high number of parameters whose input or output nature is partly unknown, high number of dependencies, as well as uncertainty and incomplete measurement data. Aside from classical modelling, basic problem solving and optimization techniques are presented. Finally, a novel submodel decomposition method is shown with an extended feature selection algorithm highlighted, along with possibilities of further development. Examples of practical application are shown to illustrate the viability of the methods.

Process planning and offline programming for robotic remote laser welding systems

The paper introduces a complete offline programming toolbox for remote laser welding (RLW) which provides a semi-automated method for computing close-to-optimal robot programs. A workflow is proposed for the complete planning process, and new models and algorithms are presented for solving the optimisation problems related to each step of the workflow: the sequencing of the welding tasks, path planning, workpiece placement, calculation of inverse kinematics and the robot trajectory, as well as for generating the robot program code. The paper summarises the results of an industrial case study on the assembly of a car door using RLW technology, which illustrates the feasibility and the efficiency of the proposed approach.

Wireless Multi-Sensor Networks for Smart Cities: A Prototype System With Statistical Data Analysis

As urbanization proceeds at an astonishing rate, cities have to continuously improve their solutions that affect the safety, health, and overall well-being of their residents. Smart city projects worldwide build on advanced sensor, information, and communication technologies to help dealing with issues like air pollution, waste management, traffic optimization, and energy efficiency. The paper reports about the prototype of a smart city initiative in Budapest, which applies various sensors installed on the public lighting system and a cloud-based analytical module. While the installed wireless multi-sensor network gathers information about a number of stressors, the module integrates and statistically processes the data. The module can handle inconsistent, missing, and noisy data and can extrapolate the measurements in time and space, namely, it can create short-term forecasts and smoothed maps, both accompanied by reliability estimates. The resulting database uses geometric representations and can serve as an information centre for public services.

Engineering education on supply-chain management for students and for employees in industry

The paper presents a virtual institute, built in the form of an Internet‐based platform, for distance learning in the field of supply‐chain management. The Institute addresses students and teachers on university educational level, as well as employees in industry. Besides learning modules, the platform provides users with means to communicate, respectively to organise and execute project activities from remote locations. Means for on‐line content editing, and course administration are made available as well.

Representation and navigation techniques for semi-structured knowledge in collaborating communities

The paper addresses problems inherent to gathering, managing and browsing knowledge relevant for maintaining and serving a collaborating group with common interests, i.e., a knowledge community. First, current solutions for information management will be examined, highlighting the need of more flexible means of information storage and retrieval. Hereafter, two of the most common—currently available—paradigms, i.e., semantic web technologies and topic maps, will be presented in an overview, and finally, the most suitable of these will be explained in a practical example.

Decision support solutions for factory and network logistics operations

The paper examines the relationship of decision levels, performance measures and modelling and decision support approaches through the example of two implemented decision support systems for manufacturing and logistics application fields. Aside from highlighting the relevance of decision support for making industrial networks fit for emerging challenges, the relevance of the two presented EU FP7 projects VFF and ADVANCE to the Factories of the Future vision is shown. A discussion of the two projects outlines future research, with particular focus on challenges that arise from integration across levels of the decision hierarchy, within an organisationally heterogeneous network.

Data type definition and handling for supporting interoperability across organizational borders

Organisational heterogeneity—especially in networks where new members may join at any time—requires ongoing actions to maintain interoperability. On the level of data interoperability, this highlights the importance of various aspects of data model and dataflow design, as well as handling of data at run-time. The latter is certain to require automated means of data model negotiation, and—while today’s design processes are far from fully automated—such means can leverage productivity and support verification procedures in data modelling and dataflow design as well. The paper presents results in one possible approach to data type definition and manipulation, through the example of the ADVANCE dataflow engine and its type-related features. Aside from an XML-based type system, type inference algorithms are presented which are employed both during design and flow execution.

From tracking operations to IOT-the small business perspective

Mapping individual items onto a virtual representation and keeping track of their properties now finds wide acceptance in larger enterprises and networks in the form of tracking and tracing. However, even if underlying technologies are ripe enough for off-the-shelf frameworks, small enterprises are still largely left unpenetrated due to present-day tracking applications still being optimized for massive use with little variability. Also, higher-level functionalities, such as inter-organizational transparency and integration of different networks - typically attributed to the ¿Internet of Things¿ concept are still awaiting wider implementation. The paper presents a track-and-trace framework along with pilot implementations focusing on the small-business sector and highlighting enhancement possibilities towards an Internet of things.