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As businesses embrace digital technologies and drive business growth, this transformation demands a reimagination of their products, processes, and work beyond just “digitalization.” The enterprise starts by capturing diverse sensor data and integrates just-in-time data to achieve “connected” stage. It further uses data along with contextual intelligence to drive integrated decisions in “collaborative” stage. It aspires to share decision making between machines and humans and evolves into “cognitive” stage. In this C3 journey—connected to collaborative, further to cognitive—enterprises need to take advantage of innovative technologies across machines, facilities, and operations in the ecosystem of products, processes, and partners. The authors highlight the nuances and opportunities across the C3 journey focusing on manufacturing value chains. Customers can orchestrate their C3 journey using innovative digital solutions outlined here for information sharing and interactive analytics that will deliver best business results with data-driven decisions.

Industry 4.0 is the latest trend in the manufacturing sector that focuses on intelligent manufacturing and smart factories. This leads to opportunities in automation, optimization, asset management and predictive maintenance, which helps reduce downtime and increase revenue. In this paper, we propose the solution that was created for a particular SMT PCB manufacturing facility in Mysuru (Vinyas IT), the features it has to offer and the methodologies that were implemented in order to achieve our goals. We will also highlight the important aspects of the solution that will be showcased during the demonstration and the impact of our solution.

Physically Unclonable Functions (PUFs) have proved to be an effective and low-cost measure against counterfeiting by providing device authentication and secure key storage services. Memory-based PUF implementations are an attractive option due to the ubiquitous nature of memory in electronic devices and the requirement of minimal (or no) additional circuitry. Dynamic Random Access Memory-- (DRAM) based PUFs are particularly advantageous due to their large address space and multiple controllable parameters during response generation. However, prior works on DRAM PUFs use a static response-generation mechanism making them vulnerable to security attacks. Further, they result in slow device authentication, are not applicable to commercial off-the-shelf devices, or require DRAM power cycling prior to authentication. In this article, we propose D-PUF, an intrinsically reconfigurable DRAM PUF based on the idea of DRAM refresh pausing. A key feature of the proposed DRAM PUF is reconfigurability , that is, by varying the DRAM refresh-pause interval, the challenge-response behavior of the PUF can be altered, making it robust to various attacks. The article is broadly divided into two parts. In the first part, we demonstrate the use of D-PUF in performing device authentication through a secure, low-overhead methodology. In the second part, we show the generation of true random numbers using D-PUF. The design is implemented and validated using an Altera Stratix IV GX FPGA-based Terasic TR4-230 development board and several off-the-shelf 1GB DDR3 DRAM modules. Our experimental results demonstrate a 4.3×-6.4× reduction in authentication time compared to prior work. Using controlled temperature and accelerated aging tests, we also demonstrate the robustness of our authentication mechanism to temperature variations and aging effects. Finally, the ability of the design to generate random numbers is verified using the NIST Statistical Test Suite.

The societal demand for inspiring and engaging science, technology, engineering, and mathematics (STEM) students and preparing our workforce for the emerging creative economy has necessitated developing students’ self-efficacy and understanding of engineering design processes from as early as elementary school levels. Hands-on engineering design activities have shown the potential to promote middle school students’ self-efficacy and understanding of engineering design processes. However, traditional classrooms often lack hands-on engineering design experiences, leaving students unprepared to solve real-world design problems. In this study, we introduce the framework of a toy design workshop and investigate the influence of the workshop activities on students’ understanding of and self-efficacy beliefs in engineering design. Using a mixed method approach, we conducted quantitative analyses to show changes in students’ engineering design self-efficacy and qualitative analyses to identify students’ understanding of the engineering design processes. Findings show that among the 24 participants, there is a significant increase in students’ self-efficacy beliefs after attending the workshop. We also identified major themes such as design goals and prototyping in students’ understanding of engineering design processes. This research provides insights into the key elements of middle school students’ engineering design learning and the benefits of engaging middle school students in hands-on toy design workshops.

In this paper, we address the applicability of Blockchain technology to ensure security of data transmitted and received by the nodes in an Internet of Things (IoT) network. We propose a Blockchain consensus model that is suitable for resource constrained devices. We also propose a model for implementing IoT security on top of the Blockchain model. We simulate our proposed model to understand its feasibility.

In this paper, we present the methodology and results from the evaluation of shapeSIFT: a multi-dimensional visualization tool for exploring part repositories in the context of eco-conscious design. The goals of this work are twofold, to create a categorization scheme for user evaluation methods specific to information visualization tools in eco-conscious design, and to formulate a user study for the shapeSIFT interface based on the developed categorization scheme. Our proposed scheme categorizes user evaluation methods based on two axes, (a) focus of the conducted user evaluation, and (b) development stage of the tool being evaluated. This scheme was used as the basis for conducting a guided formative expert review of the shapeSIFT interface with five domain experts in an industry setting. In this study we gathered experts’ comments, feedback, and usage behaviors, while they used the shapeSIFT interface to perform tasks reflective of real-world design practices. Results from the study show that shapeSIFT was easy-to-use and effective for part selection in the context of redesign. Motivated by these positive preliminary results, we intend to improve the shapeSIFT interface and conduct follow-up studies with a larger pool of designers.

A large portion of design activity involves applying previous design knowledge in order to solve new problems. Therefore, facilitating eco-conscious exploration of archived designs is needed for advancing sustainable product design. It is thus necessary to create integrated exploration tools that share common data representations for design and sustainability-related product metadata. This can allow designers to observe covariations in design data and develop engineering intuition with regards to environmental sustainability performance. In this work, we present a framework for relating sustainability and product metadata using taxonomy-based representations of lifecycle data. This facilitates simultaneous visualization of environmental indicators along with part similarities. To demonstrate this framework, we implement shapeSIFT, an interactive multidimensional visualization tool for eco-conscious design exploration. shapeSIFT uses a visual analytics-based approach to represent part metadata and environmental indicators. This facilitates query-based dynamic exploration of part repositories.

In this paper, we present a novel visualization framework for product and supply chain metadata in the context of redesign-related decision scenarios. Our framework is based on the idea of overlaying product-related metadata onto the interactive graph representations of a supply chain and its associated product architecture. By coupling environmental data with graph-based visualizations of product architecture, our framework provides a novel decision platform for expert designers. Here, the user can balance the advantages of a redesign opportunity and manage the associated risk on the product and supply chain. For demonstration, we present ViSER, an interactive visualization tool that provides an interface consisting of different mutually coordinated views providing multiple perspectives on a particular supply chain presentation. To explore the utility of ViSER, we conduct a domain expert exploration using a case study of peripheral computer equipment. Results indicate that ViSER enables new affordances within the decision making process for supply chain redesign.