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The purpose of this paper is to provide the method and system to conduct online measurement and the characterization of temperature during printed circuit board (PCB) routing process as well as the optimization of router design based on the investigation of routing temperature.

The background of this research is introduced first. Then the method to measure the routing temperature on-line by using an infrared camera is presented. The routing process is characterized by investigating the routing temperature. Tool design optimization is conducted based on the temperature in processing PCB with aluminum substrate. Finally the concluding remarks of this research are presented.

The routing temperature can be accurately measured by an infrared camera. Routing temperature is sensitive to properties of PCB, types of router and routing parameters. Very high temperature is experienced if non-appropriate routers are used to process board with aluminum substrate. It is demonstrated by the experiments that two fluted tool, three fluted tool and coated tool with three flutes are suitable for aluminum substrate processing by considering the low temperature and the nice surface finish.

The paper highlights the key points to measure the routing temperature on-line by an infrared camera and characterize the routing process and optimize the tool design by investigating the measured temperature as well.

Cold supply chain (CSC) distribution systems are vital in preserving the integrity and freshness of transported temperature sensitive products. CSC is also known to be energy intensive with a significant emission footprint. As a result, CSC requires strict monitoring and control management system during storage and transportation to improve safety and reduce profit losses. In this research, a systematic review of recent literature related to the distribution of food CSC products is presented and possible areas to extend research in modeling and decision-making are identified.

The paper analyzes the content of 65 recent articles related to CSC and perishable foods. Several relevant keywords were used in the initial search, which generated a list of 214 articles. The articles were screened based on content relevance in terms of food vehicle routing modeling and quality. Selected articles were categorized and analyzed based on cost elements, modeling framework and solution approach. Finally, recommendations for future research are suggested.

The review identified several research gaps in CSC logistics literature, where more focused research is warranted. First, the review suggests that dynamic vehicle modeling and routing while considering products quality and environmental impacts is still an open area for research. Second, there is no consensus among researchers in terms of quality degradation models used to assess the freshness of transported cold food. As a result, an investigation of critical parameters and quality modeling is warranted. Third, and due to the problem complexity, there is a need for developing heuristics and metaheuristics to solve such models. Finally, there is a need for extending the single product single compartment CSC to multi-compartment multi-temperature routing modeling.

The article identified possible areas to extend research in CSC distribution modeling and decision-making. Modified models that reflect real applications will help practitioners, food authorities and researchers make timely and more accurate decisions that will reduce food waste and improve the freshness of transported food.

This paper aims to present a broad review of near-a titanium alloys for high-temperature applications.

Following a brief introduction of titanium (Ti) alloys, this paper considers the near-α group of Ti alloys, which are the most popular high-temperature Ti alloys developed for a high-temperature application, particularly in compressor disc and blades in aero-engines. The paper is relied on literature within the past decade to discuss phase stability and microstructural effect of alloying elements, plastic deformation and reinforcements used in the development of these alloys.

The near-a Ti alloys show high potential for high-temperature applications, and many researchers have explored the incorporation of TiC, TiB SiC, Y₂O₃, La₂O₃ and Al₂O₃ reinforcements for improved mechanical properties. Rolling, extrusion, forging and some severe plastic deformation (SPD) techniques, as well as heat treatment methods, have also been explored extensively. There is, however, a paucity of information on SiC, Y₂O₃ and carbon nanotube reinforcements and their combinations for improved mechanical properties. Information on some SPD techniques such as cyclic extrusion compression, multiaxial compression/forging and repeated corrugation and straightening for this class of alloys is also limited.

This paper provides a topical, technical insight into developments in near-a Ti alloys using literature from within the past decade. It also outlines the future developments of this class of Ti alloys.

This paper's purpose is to review the design of a flip chip thermal test vehicle.

Design requirements for different applications such as thermal characterization, assembly process optimization, and product burn‐in simulation are outlined and the design processes of different thermal test chip structures including the temperature sensor and passive heaters are described in detail. The design of fireball heater, a novel test chip structure used for evaluating the effectiveness of heat spreading of advanced thermal solutions, is also explained.

Describes the design considerations and processes of the package substrate and printed‐circuit board with special emphasis on the physical routing of the thermal test chip structures. These design processes are supported with thermal data from various finite‐element analyses carried out to evaluate the capability and limitations of thermal test vehicle design.

The validation and calibration procedures of a thermal test vehicle are presented in this paper.

Wireless Body Area Network (WBAN) technology envisions a network in which sensors continuously operate on and obtained critical physical and physiological readings. Sensors deployed in WBANs have restricted resources such as battery energy, computing power and bandwidth. We can utilize these resources efficiently. By devising a mechanism that is energy efficient with following characteristics, i.e. computational complexity is less, routing overhead is minimized, and throughput will be maximum. A lot of work has been done in this area but still WBAN faces some challenges like mobility, network lifetime, transmission range, heterogeneous environment, and limited resources. In the present years well, contemplative studies have been made through a large body to reach some holistic points pertaining to the energy consumption in WBAN. Thus we/put forward appropriate algorithm for energy efficiency which can vividly corroborate the advances in this specific domain. We have also focused on various aspects and phases of the studies like study computational complexity, routing overhead and throughput type of characteristics. There is still a room for improvement to get the desired energy optimization in WBAN. The network performance mainly relies upon the algorithm used for optimization process. In this work, we intended to develop an energy optimization algorithm for energy consumption in WBAN which is based on evolutionary algorithms for inter-BAN communications using cluster-based routing protocol.

In this paper we propose a meta heuristics algorithm Goa to solve the optimization problem in WBAN. Grasshopper is an insect. Generally, this insect is viewed individually and creating large swarm in nature. Figure 5 shows the individual grasshoppers' primitive patterns in swarm. Figure 7 depicts the pseudo code of Goa. In Goa, experiments are done to view the behavior of grasshoppers in swarm. How they gradually move towards the stationary and mobile target. Through experimentation it is conceived that swarm gradually converge towards their target. Another interesting pattern related to convergence of grasshopper is that it slowly towards its target. This shows that grasshopper does not trapped in local optima. In starting iterations of exploration process Goa, search globally and in last iterations it searches local optima. Goa makes the exploration and exploitation process balanced while solving challenging optimization problems.

Energy efficiency is achieved in the optimization process of cluster formation process. As the use of proposed algorithm Goa creates the optimal number of clusters. Shorter cluster lifetime means more times clustering procedure is called. It increases the network computational cost and the communication overhead. Experimentation results show that proposed Goa algorithm performs well. We compare the results of Goa with existing optimization Algorithms ACO and MFO. Results are generated using MATLAB.

A lot of work has done for the sake of energy optimization in WBAN. Many algorithms are proposed in past for energy optimization of WBAN. All of them have some strengths and weaknesses. In this paper we propose a nature inspired algorithm Goa. We use the Goa algorithm for the sake of energy optimization in WBAN.

The purpose of the paper is to show that smart item technologies, like RFID and sensor networks, are considered the next big step in business process automation. Through automatic real‐time data acquisition, these technologies can provide benefits to a variety of industries by improving the efficiency of their operations. A service‐oriented infrastructure is proposed that enables the integration of RFID, wireless sensor networks and embedded systems technologies with existing business processes.

This paper discusses the system requirements of a smart items infrastructure in detail. Based on these requirements, the overall infrastructure and the constituting components are introduced. Also, using two real‐world scenarios, it is shown how the proposed infrastructure can be used.

The paper found a set of technical requirements for a smart items infrastructure. The research resulted in the architectural design presented.

To the best of one's knowledge, this paper is the first to identify and explain the technical requirements for a holistic smart items infrastructure. The service‐oriented system architecture provides a new approach to a flexible/adaptable infrastructure for ubiquitous computing. By pointing out requirements and open issues, the paper identifies interesting topics for future research in this area.

Considering the importance of a safe food chain for consumers and the advent of blockchain technology (BT), this research studies a food service (FS) distributor. The research aims to understand the implications related to the functional processes of distribution in FS in which it would be possible to use blockchain to achieve agility, transparency of information and improvements in food safety.

Firstly, theory regarding blockchain technology in the supply chain (BT-SC) and FS was analyzed to contextualize the theme conceptually. A single case study including 11 supply chain companies was applied in a BT implementation study in an FS distributor.

Investment in infrastructure is often identified as a barrier to adoption of BT-SC. This was, however, not found in this case. Furthermore, the validation of users was only necessary for those parties directly participating in the process or information input. Finally, findings differentiate between qualifying criteria and operational processes when considering BT projects in FS.

The findings are restricted to this single case that provided an in-depth understanding of the topic. Statistical generalization is not possible at this stage of the research.

The study is a practical example and can provide several insights to anyone looking to implement BT in their SC.

The social importance of the study lies in the importance of FS in the food sector, and by presenting ways that contribute to mitigating risks to consumers.

Real-life cases of application of BT-SC illustrate its functionalities in operational processes.

The purpose of this paper is to present a method and a system for measuring drill bit temperature on‐line in the micro drilling process and to characterize drilling processes via drill bit temperature.

The drill bit temperature measurement system was first established by the utilization of an infrared camera. Then the drill bit temperature in a drilling cycle was characterized. The temperatures of an ultra‐small micro drill bit and a coated drill bit were measured and compared.

The temperature of an ultra‐small drill bit can be measured on‐line via the proposed temperature measurement system. The drilling process can be characterized by the drill bit temperature. The drill bit temperature decreased when a coated drill bit was used.

The paper highlights key points for measuring the drill bit temperature on‐line by an infrared camera and characterizes PCB drilling processes by measuring the drill bit temperature.

The traveling purchaser problem (TPP) has gained attention in academics to deal with different variants in real business world. This study aims to study a green TPP with quantity discounts and soft time windows (TPPQS), in which a firm needs to purchase products from a set of available markets and deliver the products to a set of customers.

Vehicles are available to visit the markets, which offer products at different prices and with different quantity discount schemes. Soft time windows are present for the markets and the customers, and earliness cost and tardiness may incur if a vehicle cannot arrive a market or a customer within the designated time interval. The environmental impact of transportation activities is considered. The objective of this research is to minimize the total cost, including vehicle-assigning cost, vehicle-traveling cost, purchasing cost, emission cost, earliness cost and tardiness cost, while meeting the total demand of the customers and satisfying all the constraints. A mixed integer programming (MIP) model and a genetic algorithm (GA) approach are proposed to solve the TPPQS.

The results show that both the MIP and the GA can obtain optimal solutions for small-scale cases, and the GA can generate near-optimal solutions for large-scale cases within a short computational time.

The proposed models can help firms increase the performance of customer satisfaction and provide valuable supply chain management references in the service industry.

The proposed models for TPPQS are novel and can facilitate firms to design their green traveling purchasing plans more effectively in today’s environmental conscious and competitive market.