Developing smart services by Internet of Things in manufacturing business

Manufacturing companies have passed from selling uniquely tangible products to adopting a service-oriented approach to generate steady and continuous revenue streams. Nowadays, equipment and machine manufacturers possess technologies to track and analyze product-related data for obtaining relevant information from customers’ use towards the product after it is sold. The Internet of Things on Industrial environments will allow manufacturers to leverage lifecycle product traceability for innovating towards an information-driven services approach, commonly referred as “Smart Services”, for achieving improvements in support, maintenance and usage processes. The aim of this study is to conduct a literature review and empirical analysis to present a framework that describes a customer-oriented approach for developing information-driven services leveraged by the Internet of Things in manufacturing companies. The empirical study employed tools for the assessment of customer needs for analyzing the case company in terms of information requirements and digital needs. The literature review supported the empirical analysis with a deep research on product lifecycle traceability and digitalization of product-related services within manufacturing value chains. As well as the role of simulation-based technologies on supporting the “Smart Service” development process. The results obtained from the case company analysis show that the customers mainly demand information that allow them to monitor machine conditions, machine behavior on different geographical conditions, machine-implement interactions, and resource and energy consumption. Put simply, information outputs that allow them to increase machine productivity for maximizing yields, save time and optimize resources in the most sustainable way. Based on customer needs assessment, this study presents a framework to describe the initial phases of a “Smart Service” development process, considering the requirements of Smart Engineering methodologies.

Architecture for IoT Node and Platform

Only recently, during the past five years, consumer electronics has been evolving rapidly. Many products have started to include “smart home” capabilities, enabling communication and interoperability of various smart devices. Even more devices and sensors can be remote controlled and monitored through cloud services. While the smart home systems have become very affordable to average consumer compared to the early solutions decades ago, there are still many issues and things that need to be fixed or improved upon: energy efficiency, connectivity with other devices and applications, security and privacy concerns, reliability, and response time. This paper focuses on designing Internet of Things (IoT) node and platform architectures that take these issues into account, notes other currently used solutions, and selects technologies in order to provide better solution. The node architecture aims for energy efficiency and modularity, while the platform architecture goals are in scalability, portability, maintainability, performance, and modularity. Moreover, the platform architecture attempts to improve user experience by providing higher reliability and lower response time compared to the alternative platforms. The architectures were developed iteratively using a development process involving research, planning, design, implementation, testing, and analysis. Additionally, they were documented using Kruchten’s 4+1 view model, which is used to describe the use cases and different views of the architectures. The node architecture consisted of energy efficient hardware, FC3180 microprocessor and CC2520 RF transceiver, modular operating system, Contiki, and a communication protocol, AllJoyn, used for providing better interoperability with other IoT devices and applications. The platform architecture provided reliable low response time control, monitoring, and initial setup capabilities by utilizing web technologies on various devices such as smart phones, tablets, and computers. Furthermore, an optional cloud service was provided in order to control devices and monitor sensors remotely by utilizing scalable high performance technologies in the backend enabling low response time and high reliability.