Designs — Open Access Journal

Emerging 3D printing technologies are enabling the rapid fabrication of complex designs with favorable properties such as mechanically efficient lattices for biomedical applications. However, there is a lack of biocompatible materials suitable for printing complex lattices constructed from beam-based unit cells. Here, we investigate the design and mechanics of biocompatible lattices fabricated with cost-effective stereolithography. Mechanical testing experiments include material characterization, lattices rescaled with differing unit cell numbers, topology alterations, and hierarchy. Lattices were consistently printed with 5% to 10% lower porosity than intended. Elastic moduli for 70% porous body-centered cube topologies ranged from 360 MPa to 135 MPa, with lattices having decreased elastic moduli as unit cell number increased. Elastic moduli ranged from 101 MPa to 260 MPa based on unit cell topology, with increased elastic moduli when a greater proportion of beams were aligned with the loading direction. Hierarchy provided large pores for improved nutrient transport and minimally decreased lattice elastic moduli for a fabricated tissue scaffold lattice with 7.72 kN/mm stiffness that is suitable for bone fusion. Results demonstrate the mechanical feasibility of biocompatible stereolithography and provide a basis for future investigations of lattice building blocks for diverse 3D printed designs. Full article

Recently, more importance has been attached to consumers’ emotional feelings in the course of product design. Designers must convey positive emotions, such as surprise and affection, to consumers through their designs. For this purpose, image boards have been frequently used in design to position product emotional feeling and arouse design ideas. A large number of pictures are often needed for constructing an image board. However, it is time-consuming and labor-intensive to find appropriate pictures and the pictures that are finally collected may not reflect the expected image of consumers. Therefore, this study aims to take Lifestyles of Health and Sustainability (LOHAS) as an example to build a user-driven database for image boards. In this research, 16 LOHAS representatives were identified and recruited by using a lifestyle questionnaire to collect, and then screen out 50 proposed pictures relevant to the image of LOHAS. Since image boards are usually used by designers, in order to include their ideas, another 16 pictures were selected by the invited experienced product designers to create a comprehensive pool of 66 proposed pictures. Design experts were asked to select six key image adjectives, which included healthy, environmentally friendly, sustainable, natural, simple, and ecological for describing images of the LOHAS, from the vocabulary pool collected by general respondents, LOHAS representatives, and designers. Next, 219 LOHAS subjects were required to carry out a semantic differential assessment of each of the 66 proposed pictures with the six key images, and then two types of analyses on the collected data from the semantic differential assessment. Through mean analysis and grey correlation analysis, the recommended pictures representing LOHAS or six key adjective images were selected. The research results put forward three database application models. The results of this study are expected to be used by designers, users, manufacturers, and educators to help improve product design efficiency in the future. Full article

Due to a symbiotic relationship, economic growth leads to greater energy consumption in transportation, manufacturing, and domestic sectors. Electricity consumption in the global south is rising as nations in the region strive for economic development. Due to the high costs of fossil fuels and environmental issues, these countries are planning exploitation of their renewable energy potential for meeting their energy needs. In this paper, we take Myanmar as a case study for which photovoltaic (PV) is seen as the preferred technology owing to its modular nature and Myanmar’s tremendous PV potential. To create sustainable systems, the impact of diurnal PV profiles on electricity demand profiles needs investigating. Accurate load forecasts lead to significant savings in operation and planning and maintenance. Artificial neural networks (ANNs) can easily be used for load profile forecasting. This work proposes a three-stage systematic approach which could be employed by global south countries for designing ANN load forecasting models with the aim of simplifying the design process. While the results of this work demonstrate that PV is a suitable energy source for countries like Myanmar, they also point to the importance of including annual load increase rate and PV output degradation rate in system planning. Full article

The design methodologies and part shape algorithms for additive manufacturing (AM) are rapidly growing fields, proven to be of critical importance for the uptake of additive manufacturing of parts with enhanced performance in all major industrial sectors. The current trend for part design is a computationally driven approach where the parts are algorithmically morphed to meet the functional requirements with optimized performance in terms of material distribution. However, the manufacturability restrictions of AM processes are not considered at the primary design phases but at a later post-morphed stage of the part’s design. This paper proposes an AM design method to ensure: (1) optimized material distribution based on the load case and (2) the part’s manufacturability. The buildability restrictions from the direct energy deposition (DED) AM technology were used as input to the AM shaping algorithm to grant high AM manufacturability. The first step of this work was to define the term of AM manufacturability, its effect on AM production, and to propose a framework to estimate the quantified value of AM manufacturability for the given part design. Moreover, an AM design method is proposed, based on the developed internal stresses of the build volume for the load case. Stress tensors are used for the determination of the build orientation and as input for the part morphing. A top-down mesoscale geometric optimization is used to realize the AM part design. The DED Design for Additive Manufacturing (DfAM) rules are used to delimitate the morphing of the part, representing at the same time the freeform mindset of the AM technology. The morphed shape of the part is optimized in terms of topology and AM manufacturability. The topology optimization and AM manufacturability indicator (TMI) is introduced to screen the percentage of design elements that serve topology optimization and the ones that serve AM manufacturability. In the end, a case study for proof of concept is realized. Full article

The buzzword “smart home” promises an intelligent, helpful environment in which technology makes life easier, simpler or safer for its inhabitants. On a technical level, this is currently achieved by many networked devices interacting with each other, working on shared protocols and standards. From a user experience (UX) perspective, however, the interaction with such a collection of devices has become so complex that it currently rather stands in the way of widespread adoption and use. So far, it does not seem likely that a common user interface (UI) concept will emerge as a quasi-standard, as the desktop interface did for graphical UIs. Therefore, our research follows a different approach. Instead of many singular intelligent devices, we envision a UI concept for smart environments that integrates diverse pieces of technology in a coherent mental model of an embodied “room intelligence” (RI). RI will combine smart machinery, mobile robotic arms and mundane physical objects, thereby blurring the line between the physical and the digital world. The present paper describes our vision and emerging research questions and presents the initial steps of technical realization. Full article

Digital transformation is no longer a future trend, as it has become a necessity for businesses to grow and remain competitive in the market. The fourth industrial revolution, called Industry 4.0, is at the heart of this transformation, and is supporting organizations in achieving benefits that were unthinkable a few years ago. The impact of Industry 4.0 enabling technologies in the manufacturing sector is undeniable, and their correct use offers benefits such as improved productivity and asset performance, reduced inefficiencies, lower production and maintenance costs, while enhancing system agility and flexibility. However, organizations have found the move towards digital transformation extremely challenging for several reasons, including a lack of standardized implementation protocols, emphasis on the introduction of new technologies without assessing their role within the business, the compartmentalization of digital initiatives from the rest of the business, and the large-scale implementation of digitalization without a realistic view of return on investment. To instill confidence and reduce the anxiety surrounding Industry 4.0 implementation in the manufacturing sector, this paper presents a conceptual framework based on business process management (BPM). The framework is informed by a content-centric literature review of Industry 4.0 technologies, its design principles, and BPM method. This integrated framework incorporates the factors that are often overlooked during digital transformation and presents a structured methodology that can be employed by manufacturing organizations to facilitate their transition towards Industry 4.0. Full article

This paper presents the development of an electromagnetic energy harvester for electrical supply of a sensor unit integrated on the rotating inner ring of a rolling bearing. This energy harvester is of special interest for condition monitoring tasks on rotating shafts. A sensory monitor on the inner ring can detect wear conditions at an early stage. The harvester works without mechanical and energetic contact to surrounding components by utilizing the rotational energy of the shaft. The functionality of the Energy Harvester is enabled by the inertia principle, which is caused by an asymmetrical mass distribution. We provide simulations to validate the designs. This work includes simulation studies on the electrical power output of the harvester. Therefore, the necessary simulation of the magnetic problems is realized in a substitute simulation environment. The harvester design enables existing machines to be equipped with the harvester to provide an energy supply on rotating shafts. This clamp connection enables shaft mounting independent of location without mechanical work on the shaft. With an electrical power of up to 163.6 m W, at 3600 rpm, the harvester is used as an energy supply, which enables sensor-based monitoring of slow wear processes. Full article

This paper proposes a deep deterministic policy gradient (DDPG) based nonlinear integral backstepping (NIB) in combination with model free control (MFC) for pitch angle control of variable speed wind turbine. In particular, the controller has been presented as a digital twin (DT) concept, which is an increasingly growing method in a variety of applications. In DDPG-NIB-MFC, the pitch angle is considered as the control input that depends on the optimal rotor speed, which is usually derived from effective wind speed. The system stability according to the Lyapunov theory can be achieved by the recursive nature of the backstepping theory and the integral action has been used to compensate for the steady-state error. Moreover, due to the nonlinear characteristics of wind turbines, the MFC aims to handle the un-modeled system dynamics and disturbances. The DDPG algorithm with actor-critic structure has been added in the proposed control structure to efficiently and adaptively tune the controller parameters embedded in the NIB controller. Under this effort, a digital twin of a presented controller is defined as a real-time and probabilistic model which is implemented on the digital signal processor (DSP) computing device. To ensure the performance of the proposed approach and output behavior of the system, software-in-loop (SIL) and hardware-in-loop (HIL) testing procedures have been considered. From the simulation and implementation outcomes, it can be concluded that the proposed backstepping controller based DDPG is more effective, robust, and adaptive than the backstepping and proportional-integral (PI) controllers optimized by particle swarm optimization (PSO) in the presence of uncertainties and disturbances. Full article

The ability to fabricate functional 3D conductive elements via additive manufacturing has opened up a unique sector of ‘hybridized printed electronics’. In doing so, many of the rigid standards (i.e., planar circuit boards, potting, etc.,) of traditional electronics are abandoned. However, one critical challenge lies in producing robust and reliable interconnections between conductive inks and traditional hardware, especially when subjected to harsh environments. This research examines select material pairings for the most resilient interconnection. The method of test is wire bond pull testing that would represent a continuous strain on a connection and high acceleration testing of up to 50,000 g that would represent a sudden shock that electronics may experience in a drop or crash. Although these two environments may be similar to an overall energy exerted on the connection, the rate of force exerted may lead to different solutions. The results of this research provide insight into material selection for printed electronic interconnections and a framework for interconnection resiliency assessment, which is a critical aspect in realizing the production of next generation electronics technologies for the most demanding environments. Full article

Innovative technologies allow organizations to remain competitive in the market and increase their profitability. These driving factors have led to the adoption of several emerging technologies and no other trend has created more of an impact than Industry 4.0 in recent years. This is an umbrella term that encompasses several digital technologies that are geared toward automation and data exchange in manufacturing technologies and processes. These include but are not limited to several latest technological developments such as cyber-physical systems, digital twins, Internet of Things, cloud computing, cognitive computing, and artificial intelligence. Within the context of Industry 4.0, additive manufacturing (AM) is a crucial element. AM is also an umbrella term for several manufacturing techniques capable of manufacturing products by adding layers on top of each other. These technologies have been widely researched and implemented to produce homogeneous and heterogeneous products with complex geometries. This paper focuses on the interrelationship between AM and other elements of Industry 4.0. A comprehensive AM-centric literature review discussing the interaction between AM and Industry 4.0 elements whether directly (used for AM) or indirectly (used with AM) has been presented. Furthermore, a conceptual digital thread integrating AM and Industry 4.0 technologies has been proposed. The need for such interconnectedness and its benefits have been explored through the content-centric literature review. Development of such a digital thread for AM will provide significant benefits, allow companies to respond to customer requirements more efficiently, and will accelerate the shift toward smart manufacturing. Full article

One of the most important problems of total hip replacement is aseptic loosening of the femoral component, which is related to the changes of the stress distribution pattern after implantation of the prosthesis. Stress shielding of the femur is recognized as a primary factor in aseptic loosening of hip replacements. Utilizing different materials is one of the ordinary solutions for that problem, but using functionally graded materials (FGMs) could be better than the conventional solutions. This research work aims at investigating different porous FGM implants and a real femoral bone by a 3D finite element method. The results show that a neutral functionally graded prosthesis cannot extraordinarily make changes in the stress pattern of bone and prosthesis, but an increasing functionally graded prosthesis leads a lower level of stress in the prosthesis, and a decreasing functionally graded prosthesis can properly reduce the stress shielding among these three architectures. Due to the absence of similar results in the specialized literature, this paper is likely to fill a gap in the state-of-the-art bio-implants, and provide pertinent results that are instrumental in the design of porous femoral prostheses under normal walking loading conditions. Full article

Industry 4.0 (also referred to as digitization of manufacturing) is characterized by cyber physical systems, automation, and data exchange. It is no longer a future trend and is being employed worldwide by manufacturing organizations, to gain benefits of improved performance, reduced inefficiencies, and lower costs, while improving flexibility. However, the implementation of Industry 4.0 enabling technologies is a difficult task and becomes even more challenging without any standardized approach. The barriers include, but are not limited to, lack of knowledge, inability to realistically quantify the return on investment, and lack of a skilled workforce. This study presents a systematic and content-centric literature review of Industry 4.0 enabling technologies, to highlight their impact on the manufacturing industry. It also provides a strategic roadmap for the implementation of Industry 4.0, based on lean six sigma approaches. The basis of the roadmap is the design for six sigma approach for the development of a new process chain, followed by a continuous improvement plan. The reason for choosing lean six sigma is to provide manufacturers with a sense of familiarity, as they have been employing these principles for removing waste and reducing variability. Major reasons for the rejection of Industry 4.0 implementation methodologies by manufactures are fear of the unknown and resistance to change, whereas the use of lean six sigma can mitigate them. The strategic roadmap presented in this paper can offer a holistic view of phases that manufacturers should undertake and the challenges they might face in their journey toward Industry 4.0 transition. Full article

A central challenge in generative design is the exploration of vast number of solutions. In this work, we extend two major density-based structural topology optimization (STO) methods based on four classes of exploration algorithms of reinforcement learning (RL) to STO problems, which approaches generative design in a new way. The four methods are: first, using $\epsilon$ -greedy policy to disturb the search direction; second, using upper confidence bound (UCB) to add a bonus on sensitivity; last, using Thompson sampling (TS) as well as information-directed sampling (IDS) to direct the search, where the posterior function of reward is fitted by Beta distribution or Gaussian distribution. Those combined methods are evaluated on some structure compliance minimization tasks from 2D to 3D, including the variable thickness design problem of an atmospheric diving suit (ADS). We show that all methods can generate various acceptable design options by varying one or two parameters simply, except that IDS fails to reach the convergence for complex structures due to the limitation of computation ability. We also show that both Beta distribution and Gaussian distribution work well to describe the posterior probability. Full article

As Digital Twins gain more traction and their adoption in industry increases, there is a need to integrate such technology with machine learning features to enhance functionality and enable decision making tasks. This has lead to the emergence of a concept known as Digital Triplet; an enhancement of Digital Twin technology through the addition of an ’intelligent activity layer’. This is a relatively new technology in Industrie 4.0 and research efforts are geared towards exploring its applicability, development and testing of means for implementation and quick adoption. This paper presents the design and implementation of a Digital Triplet for a three-floor elevator system. It demonstrates the integration of a machine learning (ML) object detection model and the system Digital Twin. This was done to introduce an additional security feature that enabled the system to make a decision, based on objects detected and take preliminary security measures. The virtual model was designed in Siemens NX and programmed via Total Integrated Automation (TIA) portal software. The corresponding physical model was fabricated and controlled using a Programmable Logic Controller (PLC) S7 1200. A control program was developed to mimic the general operations of a typical elevator system used in a commercial building setting. Communication, between the physical and virtual models, was enabled using the OPC-Unified Architecture (OPC-UA) protocol. Object recognition using “You only look once” (YOLOV3) based machine learning algorithm was incorporated. The Digital Triplet’s functionality was tested, ensuring the virtual system duplicated actual operations of the physical counterpart through the use of sensor data. Performance testing was done to determine the impact of the ML module on the real-time functionality aspect of the system. Experiment results showed the object recognition contributed an average of $1.083$ s to an overall signal travel time of $1.338$ s. Full article

Customers’ needs and wants with regard to dairy products are increasingly diverse, and companies must be able to produce a variety of products. This study aimed to obtain alternative product configurations in accordance with customer requirements and to determine the types of modules required to realize the product by synergizing conjoint analysis and the decision-making trial and evaluation laboratory (DEMATEL) method. The product configuration was based on pleasurable design consisting of three aspects, namely functionality, usability, and pleasure. Pleasurable design was chosen because it involves the human in the product design as a product user so that the product design is in accordance with customer expectations. The research used the survey method with consumers of ice cream. Descriptive analysis was used to describe the product attributes desired by consumers. Orthogonal design was used to construct alternative product configurations, while the product configuration rank was determined using conjoint analysis. Based on the results of the research, the selected attributes for the functionality aspects were taste and texture, the selected attributes for the usability aspects were shape and packaging materials, and the selected attributes for the pleasure aspects were health benefits and appearance. The orthogonal design results led to 25 alternative product configurations, followed by determination of the ranking of alternative product configurations. Then the DEMATEL method was applied to analyse the relationship between the product configuration attributes to determine the types of modules that must be provided. Full article

To remain competitive in the market, it is crucial to reduce the time and costs involved in product development. Design for manufacturing and assembly is an engineering methodology that can reduce costs without compromising reliability, performance and time to market objectives. This paper presents a case study for an in-market Table Top Chain (TTC) conveyor system used by a reputed company in Saudi Arabia. TTC conveyor systems are extensively used by major food companies around the world for transporting packaged bottles, glass and cans. There are three main types of these systems, i.e., straight running, side flexing and multiflex. This work focuses on the redesign of a side flexing TTC conveyor system. The existing design of the TTC conveyor system was analysed using the DFMA 9.3 software. The outcomes of the initial analysis were utilised to redesign the TTC conveyor system for cost and design efficiency improvements. The optimum design was selected using Pugh controlled convergence method and further tested for its structural performance using finite element analysis. The redesigned model showed substantial improvements with cost reductions of 29% and an increase in design efficiency from 1.7% to 5%. Finite element analysis has also been carried out with SolidWorks 2019 to validate the structural integrity of the new concept design. Full article

Nowadays, embedded systems are increasingly complex, meaning that traditional testing methods are costly to use and infeasible to directly apply due to the complex interactions between hardware and software. Modern embedded systems are also demanded to function based on low-energy computing. Hence, testing the energy usage is increasingly important. Artifacts produced during the development of embedded systems, such as architectural descriptions, are beneficial abstractions of the system’s complex structure and behavior. Electronic Architecture and Software Tools Architecture Description Language (EAST-ADL) is one such example of a domain-specific architectural language targeting the automotive industry. In this paper, we propose a method for testing design models using EAST-ADL architecture mutations. We show how fault-based testing can be used to generate, execute and select tests using energy-aware mutants—syntactic changes in the architectural description, used to mimic naturally occurring energy faults. Our goal is to improve testing of complex embedded systems by moving the testing bulk from the actual systems to models of their behaviors and non-functional requirements. We combine statistical model-checking, increasingly used in quality assurance of embedded systems, with EAST-ADL architectural models and mutation testing to drive the search for faults. We show the results of applying this method on an industrial-sized system developed by Volvo GTT. The results indicate that model testing of EAST-ADL architectural models can reduce testing complexity by bringing early and cost-effective automation. Full article

Many different product development approaches are taught and used in engineering and management disciplines. These formalized design methods, processes, and environments differ in the types of projects for which they are relevant, the project components they include, and the support they provide users. This paper details a review of sixteen well-established product development approaches, the development of a decision support system to help designers and managers navigate these approaches, and the administration of a survey to gather subjective assessments and feedback from design experts. The included approaches—design thinking, systems thinking, total quality management, agile development, waterfall process, engineering design, spiral model, vee model, axiomatic design, value-driven design, decision-based design, lean manufacturing, six sigma, theory of constraints, scrum, and extreme programming—are categorized based on six criteria: complexity, guidance, phase, hardware or software applicability, values, and users. A decision support system referred to as the Product Development Approach Advisor (PD Advisor) is developed to aid designers in navigating these approaches and selecting an appropriate approach based on specific project needs. Next, a survey is conducted with design experts to gather feedback on the support system and the categorization of approaches and criteria. The survey results are compared to the original classification of approaches by the authors to validate and provide feedback on the PD Advisor. The findings highlight the value and limitations of the PD Advisor for product development practice and education, as well as the opportunities for future work. Full article