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The gradual commercialization of entirely autonomous vehicles is expected to bring numerous benefits, such as structural transformation in the industry. Specifically, in maritime transportation, automobile terminals that import and export finished autos are seen to transform their current loading system into a CAV (connected automated vehicle)-loading system to accommodate autonomous vehicles. In this study, the impact of introducing a CAV-loading system to a roll-on, roll-off (RORO) ports was investigated. Simulation models were developed to test the performance of the terminal with the CAV-loading system. Then, a cost model was developed to determine the economic benefits of the CAV-loading system. The results in this study revealed that operating costs were reduced by 90%, while terminal operations were significantly improved. In addition, the study revealed that using the CAV-loading system resulted in a 12% reduction in CO2 emissions compared to that using the current loading system. The originality of this study lies in its transformative potential for an industry that heavily relies on human labor and has limited mechanization and automation. This study provides significant implications for incorporating autonomous vehicles in planned automobile terminal operations. [ABSTRACT FROM AUTHOR]

The manufacturing landscape is ever-changing, and one of the most significant driving forces is the emergence of additive manufacturing (AM), which enables cost-effective and small-scale production towards sustainability. To better align AM with manufacturing in suitable applications, this study proposes a business model in terms of the cost pattern and scaling production supported by three key concepts: standardisation, localisation and collaboration. The ambiguity of the cost calculation is one of the key factors slowing down AM progress, and a lack of a cost pattern affects decision-making when applying AM to appropriate applications. The business model in this study is focused on applying the data collected from previous research, the collection-recycling-manufacturing (CRM) model, to discover the implications of AM processes on the road to sustainable manufacturing. The novel business model envisions the nature of AM characteristics and their linkages to cost patterns, so AM applications can be integrated into a cost-effective process. This study contributes qualitative analysis to the cost patterns' integration. Through this integration, the business model mediates the gap between technologies and applications via the formulas of cost patterns, so AM can perform its appropriate role in the industry mainstream. The cost modelling proposed in this study derives generic formulas via the unit cost of tooling, moulding, machine, materials, design, miscellaneous cost and the batch size. The business model applies the "divide-and-conquer" concept, convergence effect and data analysis to support quantitative analysis. The model can calculate the total cost per unit, and its accuracy is close to 100%. Through the novelty of this model, AM and conventional manufacturing (CM) cost benchmarking and decision support functions are enabled to aid in stakeholder decision-making. Eventually, appropriate AM technologies and processes can synchronise with localisation, standardisation and collaboration and, ultimately, the impact of AM towards sustainable manufacturing. [ABSTRACT FROM AUTHOR]

This paper is concerned with the analysis of an infinite-capacity batch arrival multi-server queueing system with Bernoulli feedback, synchronous multiple and single working vacation policies, waiting servers, reneging and retention of reneged customers. The steady-state solution of the queueing system is obtained by using probability generating function (PGF). In addition, important performance measures of the queueing system are derived. Then, a cost model is formulated in order to carry out the parameter optimization using genetic algorithm (GA). Finally, numerical study is presented in which various system performance measures are evaluated based on supposed numerical values given to the system parameters. [ABSTRACT FROM AUTHOR]

Engineering design shows a growing interest in exploring cost analysis to anticipate manufacturing issues and integrate production aspects within the product development process. This research aims to highlight key elements (inputs, parameters, models) to accurately predict the cost of a forged part using a complete model, with important information that can be available during the design phase. For this purpose, a systematic literature review of existing engineering methodologies developed for cost analysis of forged parts (i.e., cost estimation, DtC, and ABC) was performed with characterizations of the different approaches for evaluating the most important topics related to this objective. As a result, the most important insights related to the aim of this review are provided: (i) among quantitative methods, analytical and parametric models are the most suitable approaches to develop a cost estimation, (ii) a cost model based on a linear equation supported by single or multiple variables seems to be the most accurate tool to establish a robust cost analysis in the design of forged components, and (iii) input parameters related to the material type and geometrical features are the most critical cost-drivers in the cost assessment. Moreover, this review contributes to identifying emerging applications and obsolete topics, providing the ground to investigate unexplored areas relevant to future research. [ABSTRACT FROM AUTHOR]

Stone sawing industry is among the most important mineral industries in Iran. Therefore, special attention to this sector can result in economic growth by providing a healthy condition in competition with other countries. Two important factors, which affect the world market's competition, are the cost operation and the quality of the processed stone. Providing economic advantage by lowering the cost without causing any defect in the quality of the stone is the key point in the industry. Therefore, in this research, an economic evaluation was carried out on the sawing process of a hard stone and a cost model including all cost factors was developed. Then, in order to determine the most effective cost factors, sensitivity analysis was performed on the proposed model. The results of this study showed that diamond disk and energy cost are respectively the most important factors in the operation. [ABSTRACT FROM AUTHOR]

Manufacturing engineers are frequently asked to select the best process for creating components but often the judgement is qualitative rather than quantitative. This paper presents a methodology (DCFA – Differential Cost and Feasibility Analysis) for assessing the technological and economic feasibility of using Near Net Shape (NNS) processes for the manufacturing of specific components. The methodology examines changes in raw material usage and finish processes (e.g. machining processes) that would result from adaption of a new manufacturing process. To illustrate the method, a case study that assesses the feasibility of using centrifugal casting for the production of valve cages is detailed. The case study concludes that the application of this process to the current manufacturing lines could result in significant cost reductions (particularly in machining time and reduction of scrappage). The feasibility methodology is generic and can potentially be used to investigate the application of a broad range of NNS processes in general manufacturing applications. Further, the developed cost models also allow the economic impact of a new process to be assessed, even at the early stages of product design. [ABSTRACT FROM PUBLISHER]

For efficient large-scale Web crawlers, URL duplication checking is an important technique since it is a significant bottleneck. In this paper, we propose a new URL duplication checking technique for a parallel Web crawler; we call it full-coverage two level URL duplication checking (full-coverage-2L-UDC). Full-coverage-2L-UDC provides efficient URL duplication checking while ensuring maximum coverage. First, we propose two-level URL duplication checking (2L-UDC). It provides efficiency in URL duplication checking by communicating at the Web site level rather than at the Web page level. Second, we present a solution for the so-called coverage problem, which is directly related to the recall of the search engine. It is the first solution for the coverage problem in the centralized parallel architecture. Third, we propose an architecture, FC2-LUDCbot, for a centralized parallel crawler using fiill-coverage-2L-UDC. We build a seven-agent FC2L-UDCbot for extensive experiments. We show that the crawling speed of FC2L-UDCbot is approximately proportional to the number of agents (i.e., FC2L-UDC-bot is faster than a single-machine crawler by 6.9 times). Full-coverage-2L-UDC allows FC2L-UDCbot to be scalable to the number of agents since it effectively deals with the overheads incurred in a parallel environment. Through an in-depth analysis, we construct a cost model for estimating the crawling speed of a scaled-up crawler. Using the model, we show that FC2L-UDCbot can crawl Google-scale Web pages within several days using dozens of agents. [ABSTRACT FROM AUTHOR]

This paper presents the development and realization of the ' Integrated system for analyzing Maintenance records in Product improvement' (IMaPro). IMaPro has been designed based on research and need analysis through literature survey and consultation with industry partners in Germany. The primary goal is to analyze structured feedback data, such as condition monitoring, service, and customer data, especially to discover improvement potentials in maintenance management and ultimately product improvement. In this context, Bayesian network utilizes the knowledge-based analysis of feedback data. The Bayesian network is used in combination of a mathematical cost model. The model supports cost-based monitoring and controlling of maintenance activities, and consequently leads to the identification of the lack and applying the lessons learned for improving maintenance costing. The concept has been validated and pilot-tested through the use of a sample product, namely block heater system. Furthermore, IMaPro incorporates an in-house development of mobile application for acquisition of service data. [ABSTRACT FROM AUTHOR]

The goal of this paper is to show that the implementation of the queuing theory could set an optimal capacity of the port container terminal, or a combination of the number of berths and cranes per berth with the minimum costs for the given traffic. The container terminal is a system composed of a specific number of mutually depending subsystems so the optimal capacity of the terminal is reduced to the calculation of the optimal number of berths, since the capacity of the berth determines the necessary capacity of the other subsystems, and thereby a throughput of the entire container terminal. The optimal solution was received by applying a model of total costs that is based on the queuing theory. This model can be used for any container terminal and for terminals in present and future conditions. The results are a basis for bringing adequate business decisions related to the operating of the terminal. The model is tested on an example of container terminal Brajdica in Port of Rijeka. [ABSTRACT FROM AUTHOR]