Various industries are undergoing transformation given recently available pervasive sensors, low-cost and low-latency digital communication, and distributed control technologies. The objective of this paper is to support the introduction of Internet of things (IoT) technologies in the maritime industry. The maritime industry is analyzed as a system of systems to define performance criteria and functions to be modeled and analyzed through simulation. In this case, the simulation of a shipping system includes models of operation, cargo loading, fuel loading, and docking for maintenance. In the simulation, various kinds of IoT technologies are defined by several input parameters. By changing the parameters, the simulator evaluates the impact of those technologies quantitatively. As a case study, 11 IoT technologies are evaluated and compared. The result reveals several insights that weight of the ship is the most impactful for the profit, controlling damage of the ship's hull by operation is the most important for safety, and improvement in efficiency at ports is the key to reducing delay time in operation. Moreover, this paper shows that the sensitivity analysis by changing the input parameters can support the decision making of how much investment will be effective in considering the technologies' levels.
For software development, especially massive software systems, a waterfall process is used traditionally. A waterfall process can be highly effective on the condition that a master plan is fixed and the possibility of changes and uncertain rework is low. However, in software development projects, many kinds of reworks occur corresponding to uncertain requirement changes and program bugs. In addition, with the advent of cloud-based software platforms and continuous development operations, it is possible to develop a software system while operating the system. To respond to this situation, software development projects often adopt an agile process. Agility may allow conditional response to uncertain rework, yet at the same time it may be difficult to control the achievement of known project targets. Recently, many cases of adopting mixed processes including waterfall and agile have been reported in the massive software development projects. In this paper, we argue that the mixed process architecture should be designed, considering the scale of the targeted software project, the culture of organization, the probability of uncertain requirement changes, and so on. This paper proposes a methodology of evaluating the impact of waterfall, agile, and mixed project architectures by using process simulation. A project architectural approach is evaluated with a simulator which includes a software reliability growth model and uncertain rework driven by requirement change and error propagation. The proposed methodology was applied to a development project for a simple shopping website. The results showed that the proposed methodology allows exploration of partial agile adoption depending on the nature of the system development project, including its scale and chances of change. For example, in this paper, if the scale of the project is small, the positive effect of increasing agility by adopting agile processes is low. On the other hand, if the scale of the project is large, the effect of increasing agility by adopting agile process can increase. Furthermore, it became clear that it is important to not apply an agile process blindly, but instead to design a mixed project architecture considering the number of errors and development schedule targets across the project scope.
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