Industry 4.0 is based on the digitization of manufacturing industries and has raised the prospect for substantial improvements in productivity, quality, and customer satisfaction. This digital transformation not only affects the way products are manufactured but also creates new opportunities for the design of products, processes, services, and systems. Unlike traditional design practices based on system-centric concepts, design for these new opportunities requires a holistic view of the human (stakeholder), artefact (product), and process (realization) dimensions of the design problem. In this paper we envision a “human-cyber-physical view of the systems realization ecosystem,” termed “Design Engineering 4.0 (DE4.0),” to reconceptualize how cyber and physical technologies can be seamlessly integrated to identify and fulfil customer needs and garner the benefits of Industry 4.0. In this paper, we review the evolution of Engineering Design in response to advances in several strategic areas including smart and connected products, end-to-end digital integration, customization and personalization, data-driven design, digital twins and intelligent design automation, extended supply chains and agile collaboration networks, open innovation, co-creation and crowdsourcing, product servitization and anything-as-a-service, and platformization for the sharing economy. We postulate that DE 4.0 will account for drivers such as Internet of Things, Internet of People, Internet of Services, and Internet of Commerce to deliver on the promise of Industry 4.0 effectively and efficiently. Further, we identify key issues to be addressed in DE 4.0 and engage the design research community on the challenges that the future holds.

Many different additive manufacturing (AM) technologies enable the realization of prototypes and fully-functional artifacts. Although very different in solution principle and embodiment, significant functional commonality exists among the technologies. This commonality affords the authors an opportunity to propose a new classification framework for additive manufacturing technologies. Specifically, by following the systematic abstraction approach proposed by the design methodology of Pahl and Beitz, the authors first identify the working principles of each AM process. A morphological matrix is then employed to functionally present these principles such that commonalities between processes can be identified. In addition to using it as a means of classifying existing processes, the authors present the framework as a tool to aid a designer in the conceptual design of new additive manufacturing technologies. The authors close the paper with an example of such an implementation; specifically, the conceptual design of a novel means of obtaining metal artifacts from three-dimensional printing.

A material's design revolution is underway with a focus to design the material microstructure and processing paths to achieve certain performance requirements of products. A host of manufacturing processes are involved in producing a product. The processing carried out in each process influences its final properties. To couple the material processing-structure-property-performance (PSPP) spaces, models of specific manufacturing processes must be enhanced and integrated using multiscale modeling techniques (vertical integration) and then the input and output of the various manufacturing processes must be integrated to facilitate the flow of information from one process to another (horizontal integration). Together vertical and horizontal integration allows for the decision-based design exploration of the manufacturing process chain in an inverse manner to realize the end product. In this paper, we present an inverse method to achieve the integrated design exploration of materials, products, and manufacturing processes through the vertical and horizontal integration of models. The method is supported by the concept exploration framework (CEF) to systematically explore design alternatives and generate satisficing design solutions. The efficacy of the method is illustrated for a hot rod rolling (HRR) and cooling process chain problem by exploring the processing paths and microstructure in an inverse manner to produce a rod with specific mechanical properties. The proposed method and the exploration framework are generic and support the integrated decision-based design exploration of a process chain to realize an end product by tailoring material microstructures and processing paths.

The steel manufacturing process is characterized by the requirement of expeditious development of high quality products at low cost through the effective use of available resources. Identifying solutions that meet the conflicting commercially imperative goals of such process chains is hard using traditional search techniques. The complexity in such a problem increases due to the presence of a large number of design variables, constraints and bounds, conflicting goals and the complex sequential relationships of the different stages of manufacturing. A classic example of such a manufacturing problem is the design of a rolling system for manufacturing a steel rod. This is a sequential process in which information flows from first rolling stage/pass to the last rolling pass and the decisions made at first pass influence the decisions that are made at the later passes. In this context, we define horizontal integration as the facilitation of information flow from one stage to another thereby establishing the integration of manufacturing stages to realize the end product. In this paper, we present an inverse design method based on well-established empirical models and response surface models developed through simulation experiments (finite-element based) along with the compromise decision support problem (cDSP) construct to support integrated information flow across different stages of a multistage hot rod rolling system. The method is goal-oriented because the design decisions are first made based on the end requirements identified for the process at the last rolling pass and these decisions are then passed to the preceding rolling passes following the sequential order in an inverse manner to design the entire rolling process chain to achieve the horizontal integration of stages. We illustrate the efficacy of the method by carrying out the design of a multistage rolling system. We formulate the cDSP for the second and fourth pass of a four pass rolling chain. The stages are designed by sequentially passing the design information obtained after exercising the cDSP for the last pass for different scenarios and identifying the best combination of design variables that satisfies the conflicting goals. The cDSP for the second pass helps in integrated information flow from fourth to first pass and in meeting specified goals imposed by the fourth and third passes. The end goals identified for this problem for the fourth pass are minimization of ovality (quality) of rod, maximization of throughput (productivity), and minimization of rolling load (performance and cost). The method can be instantiated for other multistage manufacturing processes such as the steel making process chain having several unit operations.