摘要：Nowadays, issues on population, environment and resource have become the world’s attentive focus. Sustainable development has been widely accepted around the world. As one of the biggest waste generator and resources consumer, manufacturing industry is facing more challenges as well as opportunities. In order to reduce both resource consuming and waste discharging effectively, traditionally manufacturing mode should be improved. Newly emerged creative technologies and strategies, including green design, green manufacturing and cleaner production, are regarded as the radical resolvent for current environment and resource issues and they will be the only way in the future that manufacturing will evolve. In this paper, a serial of research on green design/manufacturing and cleaner product theoretically and practically was presented. These creative technology and strategy will give strong support to ‘green’ the whole electromechanical designing and manufacturing processes.

摘要：Revolutionary breakthroughs in artificial intelligence (AI) and machine learning (ML) have had a profound impact on a widerange of scientific disciplines, including the development of artificial cell factories for biomanufacturing. In this paper, wereview the latest studies on the application of data-driven methods for the design of new proteins, pathways, and strains. Wefirst briefly introduce the various types of data and databases relevant to industrial biomanufacturing, which are the basis fordata-driven research. Different types of algorithms, including traditional ML and more recent deep learning methods, are alsopresented. We then demonstrate how these data-based approaches can be applied to address various issues in cell factorydevelopment using examples from recent studies, including the prediction of protein function, improvement of metabolicmodels, and estimation of missing kinetic parameters, design of non-natural biosynthesis pathways, and pathway *** the last section, we discuss the current limitations of these data-driven approaches and propose that data-driven methodsshould be integrated with mechanistic models to complement each other and facilitate the development of synthetic strains forindustrial biomanufacturing.

摘要：This paper presents a part count tool that predicts the part count for a particular product concept during the conceptual design phase. The part count tool will also aid in ranking the design concepts by the criterion of number of components for a product. This tool utilizes existing automated concept generation algorithms to generate the design concepts. It extracts the available data from the Design Engineering Lab Design Repository to determine an average number of parts per component type in the repository and then calculates an average part count for new concepts. The part count tool also uses an algorithm to determine how to connect two non-compatible components through the addition of mutually compatible components. While emphasis is placed on the average parts per product in evaluating designs, the overall functional requirement of the product is also considered.

摘要：Custom-made esthetic finger prostheses, which are used for rehabilitation of patients with missing or impaired fingers, have been fabricated manually. However, such fabrication is time-consuming and requires manual skill. Here we propose a computer-aided method for fabricating finger pros-theses to save time and allow fabrications that do not require considerable manual skill. In this method, the dimensions of a patient’s healthy finger on the contralateral hand are first measured using a caliper. Using these dimensions, a three-dimensional model is constructed for fabricating a prosthesis for the patient’s impaired finger. Using the 3D model, a mold is designed using 3D modeling tools and a computer-aided design system. The resulting mold is then fabricated using a 3D printer. A finger prosthesis is fabricated by pouring silicone resin into the mold. A finger prosthesis for a volunteer was experimentally fabricated according to the proposed method. To evaluate the size and shape of the finger prosthesis, the difference between the finger prosthesis and the original finger of the volunteer was analyzed. Because the average difference between them was 0.25 mm, it was concluded that the proposed method could be used to fabricate a finger prosthesis of adequate size and shape.

摘要：The DOE methodology is an effective tool for upgrading the level of measurement and assessment. In any design, planning or control problem the designer is faced with many alternatives. He/she is challenged to develop design approaches that can meet both quality and cost criteria. The way experiments are designed greatly affects the effective use of the experimental resources and the easiness with which the measured results can be analyzed. This paper does not present new evidence based on designed experiments. Its objective is solely to show how useful application of multifactor experiments is in a variety of circumstances and decision making scenarios. The paper reviews three published examples where this method was used in different contexts: quality control, flexible manufacturing systems (FMS) and logistics systems. The physical experiment has been carried out to improve the quality of a special type of batteries. The simulation experiment has been carried out to investigate the impact of several flexibility factors in a flexible manufacturing system. The numerical value of a complex analytical expression representing a customer oriented logistics performance measure has been calculated for different values of its parameters, i.e. the given numerical values of the investigated factors. It enabled a methodical examination of all factor effects and especially their interactions, thus shedding light on complex aspects of the logistics decision problem. In these examples, cases from different contexts were presented, enabling to view design of experiments as a powerful ingredient for improving decision making in a variety of circumstances.