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This paper aims to describe the idea behind and design of a miniaturized distributed measurement system based on a controller area network (CAN) data bus.

The intention of the designers was to build a light and modular measurement system which can be used in remotely piloted aircraft systems and ultra-light aircraft during flight tests, as well as normal operation. The structure of this distributed measurement system is based on a CAN data bus. The CAN aerospace standard has been applied to the software as well as the hardware comprising this system. PRP-W2 software designed for PCs is an additional component of the proposed measurement system. This software supports data acquisition from a recorder unit and allows for preliminary data analysis, as well as data conversion and presentation.

The system, complete with a high-speed data recorder, was successfully installed on board of an MP-02 Czajka aircraft. A research experiment using the system and oriented on airframe high frequency vibration analysis is presented in the final part of this paper.

This measurement system allows analysis of high-frequency vibrations occurring at selected points of the aircraft. A data set is recorded by three-axis accelerometers and gyroscopes at frequencies up to 1 kHz.

The use of a miniature and lightweight modular measurement system will, in many cases, be faster and less expensive than full-scale measurement and data acquisition systems, which often require a lengthy assembly process. The implementation of this class of lightweight flight test systems has many advantages, in particular to the operation of small aircraft. Such solutions are likely to become increasingly common in unmanned aerial vehicles and in other light aircraft in the future.

The adaptation of a distributed measuring system with a high frequency of measurements for purposes of small and miniature aircraft.

The purpose of this paper is to develop a preliminary conceptual scale for the measurement of distributed manufacturing (DM) capacity of manufacturing companies operating in rubber and plastic sectors.

A two-step research methodology is employed. In first step, the dimensions of DM and different levels of each dimension have been defined. In second step, an empirical analysis (cluster analysis) of database firms is performed by collecting the data of 38 firms operating in Italian mould manufacturing sector. Application case studies are then analyzed to show the use of the proposed DM conceptual scale.

A hyperspace, composed of five dimensions of DM, i.e. manufacturing localization; manufacturing technologies; customization and personalization; digitalization; and democratization of design, is developed and a hierarchy is defined by listing the levels of each dimension in an ascending order. Based on this hyperspace, a conceptual scale is proposed to measure the positioning of a generic company in the DM continuum.

The empirical data are collected from Italian mould manufacturing companies operating in rubber and plastic sectors. It cannot be assumed that the industrial sectors in different parts of the world are operating under similar operational, regulatory and economic conditions. The results, therefore, might not be generalized to manufacturing companies operating in different countries (particularly developing countries) under different circumstances.

This is first preliminary scale of its kind to evaluate the positioning of companies with respect to their DM capacity. This scale is helpful for companies to compare their capacity with standard profiles and for decision making to convert the existing manufacturing operations into distributed operations.

Fixture failures are the main cause of the dimensional variation in the assembly process. The purpose of this paper is to focus on the optimal sensor placement of compliant sheet metal parts for the fixture fault diagnosis.

Based on the initial sensor locations and measurement data in launch time of the assembly process, the Bayesian network approach for fixture fault diagnosis is proposed to construct the diagnostic model. Furthermore, given the desired number of sensors, the diagnostic ability of the sensor set is evaluated based on the mutual information of the nodes. Thereby, a new sensor placement method is put forward and validated with a real automotive sheet metal part.

The new proposed method can be used to perform the fixture fault diagnosis and sensor placement optimization effectively, especially in a data‐rich environment. And it is robust in the presence of measurement noise.

This paper presents a novel approach for fixture fault diagnosis and optimal sensor placement in the assembly process.

Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control methods play an essential role in the quality improvement of assembly products. This paper aims to review the development of data-driven modeling methods for process monitoring and fault diagnosis in multi-station assembly systems. Furthermore, the authors discuss the applications of the methods proposed and present suggestions for future studies in data mining for quality control in product assembly.

This paper provides an outline of data-driven process monitoring and fault diagnosis methods for reduction in variation. The development of statistical process monitoring techniques and diagnosis methods, such as pattern matching, estimation-based analysis and artificial intelligence-based diagnostics, is introduced.

A classification structure for data-driven process control techniques and the limitations of their applications in multi-station assembly processes are discussed. From the perspective of the engineering requirements of real, dynamic, nonlinear and uncertain assembly systems, future trends in sensing system location, data mining and data fusion techniques for variation reduction are suggested.

This paper reveals the development of process monitoring and fault diagnosis techniques, and their applications in variation reduction in multi-station assembly.

This paper focuses on the development of a distributed rapid prototyping system via the Internet to form a framework of Internet prototyping and manufacturing for the support of effective product development. The proposed methodology is targeted at a wide audience using a disparate range of computer systems to access remotely located rapid prototyping facilities via the Internet for prototype fabrication. The methodology is useful for both educational research for teaching evolving rapid prototyping technologies and remote scientific visualization. This approach is based on the merger of object‐oriented modular software architecture and client server communications for the remote control of rapid prototyping hardware (called fused deposition modeling) via the Internet. Other Web tools are used to allow the remote user to have higher interactivity with the server applications that have a direct link with the front‐end terminals controlling the rapid prototyping hardware.

The assessment of the quality of the electric power supply, as well as that of the electric loads, is becoming a critical problem, especially when the liberalization of the electricity market is involved. Power quality can be evaluated by means of a number of quantities and indices whose measurement is not straightforward and is generally attained by means of digital signal processing techniques based on complex algorithms. The assessment of the uncertainty of the results of such measurements is a critical, open problem. This paper proposes a general purpose approach, based on the Monte Carlo method that, starting from the estimated contributions to the uncertainty of each device in the measurement chain, estimates the probability density distribution of the measurement result, and therefore, its standard uncertainty. This approach has been experimentally validated for the active power measurement and applied to the estimation of the uncertainty of the measurement of more complex power quality indices.

This paper will focus on the implications for value chain performance measures arising from the rapidly emerging requirement for agility both within individual business units and across sophisticated manufacturing value chains. Recent developments in the way companies are expected to respond to rapid and unpredictable change in the external environment have resulted in new paradigms for manufacturing which comprise a combination of leanness, agility and virtual enterprises. The primary focus of academic researchers has been in the area of determining how agility is attained in order that organisational structures can best be designed. However, the concept that “what you measure is what you get” is equally valid for virtual organisations as it has always been for stand‐alone manufacturing businesses. This paper therefore discusses the requirements for new approaches to performance measures and raises some of the issues that need to be developed further in support of the concept of agility.

This paper aims to present a review of the design and development of the turbidimeter for measuring the turbidity level in water. Monitoring the turbidity level of water is important because it is related to public health.

A precise and reliable turbidimeter can provide vital data that reveals the water condition level. Several turbidimeter units are discussed briefly. Three types of turbidimeter design – single beam, ratio and modulated four beams – are elaborated with some illustrations of the design concept. Various improvements and innovations for upgrading turbidimeter design are also discussed.

This paper elaborated on a new method of estimating the water turbidity level in water samples using an optical tomography system based on the independent component analysis method. The results showed that a tomography-based turbidimeter can measure slight changes in the level of turbidity when the volume of contaminants is changed slightly. The turbidimeter can also provide a profile of the distribution of the turbidity in the water sample.

A turbidimeter based on the optical tomography concept can be a valuable tool in determining the level of pollution in rivers, sea, etc.

The main purpose of the present study was to improve and develop previously proposed models for Iran telecommunication networks. It should be noted that the six-dimensional (6D) sustainability model used in this study will be a useful and comprehensive model for industries. Since, the new dimension of IT along with the five well-known economic, social, environmental, technical and institutional aspects of organizations is considered to have great impacts on supply chain sustainability; the proposed framework can be practical.

According to the related literature review, there are two research streams in supply chain management. The first stream is exploratory research, seeking out conceptual discussions in this area. The second one is associated with mathematical models and techniques, aiming to set decision-making rules in this regard (Agrell et al., 2004). In this study, evaluation was performed using the FMEA method as an analytical technique based on the principle of pre-occurrence prevention to identify potential failure factors in sensitive systems (Mohammadfam and Kianfari, 2008).

After identifying the risks and causes of the incidence and effects and consequences of risks, preventive and risk control measures and advisory strategies were presented. Customers with 45.76% share in critical risks are threatening to maintain supply chain in these companies. During this study, it was found that 33.9% of the main source of supply chain critical risks was customers, constituting 45.76% of such risks, accompanied by organization, having a 38.88% share of critical risk generation. The study findings also revealed that 33.9% of critical risks were mainly (equally) related to economic and technical aspects of supply chain sustainability in telecommunication networks. Moreover, as a newly-introduced sixth dimension, IT represented 10.17% of critical risks threatening supply chain sustainability in such networks. Critical risks are mainly related to the economic and technical aspects (equally) with the sustainability of the telecommunication networks supply chain. Also, as a new finding and the sixth dimension, 10.17% of the critical risks that threaten the sustainability of the telecommunication networks supply chain have the information technology dimension.

The internet and fixed and mobile data services are provided by several private companies in Iran, which are relatively similar in terms of their supply chains. In order to manage the sustainability of Iran's telecommunication supply chain, telecommunication networks affiliated to Iran Telecommunication Company (ITC), operating in the field of data and internet services and fixed telephone were selected in 31 provinces. The intended networks were also providing an important part of the country's needs including Mobile Telecommunication Company of Iran, a subsidiary of Iran's telecommunication networks, as one of the top companies in this industry. Accordingly, all the networks studied in this study needed to be identified with regard to communication sustainability risks, since they provide management solutions to each other by segregating risks. In this study, 68 managers and 72 experts participated in different work teams of telecommunication networks.

The use of frequency output for measurement transmission remains common in the design of smart transmitters. Conventional methods of frequency generation, based on counting clock cycles, have a precision which is inversely proportional to the frequency to be generated. Consequently, frequency output precision could be much lower than the measurement precision. This paper describes a simple frequency generation technique which, when implemented in low‐cost hardware, provides a precision of 10⁻⁶ per cent for all frequencies. The method represents an intermediate non‐available frequency by dithering between two exact frequencies. Averaging over some reasonably short timescale provides the desired frequency to high precision.