دانلود رایگان مقاله انگلیسی طراحی معماری تحلیلی کلان داده ها - کاربردها در سیستم های تولیدی - الزویر 2018

Abstract

Context: The rapid prevalence and potential impact of big data analytics platforms have sparked an interest amongst different practitioners and academia. Manufacturing organisations are particularly well suited to benefit from data analytics platforms in their entire product lifecycle management for intelligent information processing, performing manufacturing activities, and creating value chains. This requires re-architecting their manufacturing legacy information systems to get integrated with contemporary data analytics platforms. A systematic re-architecting approach is required incorporating careful and thorough evaluation of goals for data analytics adoption. Furthermore, ameliorating the uncertainty of the impact the new big data architecture on system quality goals is needed to avoid cost blowout in implementation and testing phases. Objective: We propose an approach to reason about goals, obstacles, and to select suitable big data solution architecture that satisfy quality goal preferences and constraints of stakeholders at the presence of the decision outcome uncertainty. The approach will highlight situations that may impede the goals. They will be assessed and resolved to generate complete requirements of an architectural solution. Method: The approach employs goal-oriented modelling to identify obstacles causing quality goal failure and their corresponding resolution tactics. It combines fuzzy logic to explore uncertainties in solution architectures and to find an optimal set of architectural decisions for the big data enablement process of manufacturing systems. Result: The approach brings two innovations to the state of the art of big data analytics platform adoption in manufacturing systems: (i) A systematic goal-oriented modelling for exploring goals and obstacles in integrating manufacturing systems with data analytics platforms at the requirement level and (ii) A systematic analysis of the architectural decisions under uncertainty incorporating stakeholders’ preferences. The efficacy of the approach is illustrated with a scenario of reengineering a hyper-connected manufacturing collaboration system to a new big data architecture.

Conclusion, research limitations, and further work

Legacy manufacturing systems are expected to be able to utilize data analytics platforms for advanced information analytics. A clear understanding of goals and risks against data analytics adoption and how they relate to manufacturing systems is particularly crucial. As a business risk management strategy, a systematic architecture design to enable existing manufacturing systems to use data analytics platforms is an important contribution. Our goal-obstacle analysis which takes into account imperfect information and unavoidable uncertainties is quite intuitive to follow. In particular, it provides an early stage analysis, which is taken place before delving into technical aspects of implementing a big data analytics architecture. To the best of our knowledge, such a harness is not available in the literature. Our approach applies goal reasoning and fuzzy-based logic for analysing suitability of big data solution architecture for manufacturing systems. The approach starts with identifying high-level architectural goals, architectural decision alternatives to realize these goals, generating probable obstacles, and analysing uncertainties in selecting solution architectures. The output of the approach gives the system architect a complete set of architectural requirements to be incorporated into the implementation stage of data analytics architecture implementation to make appropriate trade-offs based on, for instance, cost, security, or performance goals. The application of the approach was also demonstrated the in a scenario of moving ETL to a set of data analytics platforms. Apart from manufacturing and big data settings, due to the genericity of the approach, it can be used in other scenarios of technology adoption when the system architect is interested in evaluating possible solution architecture alternatives.