AN INFORMATION MODEL IN THE DOMAIN OF DISASSEMBLY PLANNING FOR SUSTAINABLE MANUFACTURING

Disassembly, a process of separating the End of Life (EOL) product into discrete components for re-utilizing their associated residual values, is an important part for the sustainable manufacturing. This work focuses on the modeling of the disassembly planning related information, and develops a Disassembly Information Model (DIM) based on an extensive investigation of various informational aspects of the disassembly planning. The developed Disassembly Information Model, which represents an appropriate systematization and classification of the products, processes, uncertainties and degradations related information, follows a layered modeling methodology. In this layered configuration, the DIM is subdivided into three distinct layers with an intent to separate general knowledge into different levels of abstractions, and to reach a balance between information reusability and information usability. The performance evaluation of the DIM (usability and reusability) is accessed by successful implementations of the DIM model into two prototype software applications in the domain of disassembly planning. The first application, called the Disassembly Sequence Generator (DSG), identifies the optimal disassembly sequence using a CAD based searching algorithm and a disassembly Linear Programming (LP) model. The searching process results in an AND/OR graph, which represents all the feasible disassembly sequences of a specific EOL product; whereas the LP model takes the AND/OR graph as an input and determines the economically optimal process sequence among all the possibilities. The second application is called the Adaptive Disassembly Planning (ADP), which further takes the EOL product uncertainty and degradation issues into consideration. In order to address these issues, fuzzy logic and Bayesian Network methodologies are used to develop a Disassembly Decision Network (DDN), which adaptively generates the optimal disassembly sequence based on the current available information. This research work is the first attempt to develop a comprehensive Information Model in the domain of disassembly planning. The associated modeling methodology that has been developed in this research is generic and scalable, and it could be widely adopted in other engineering domains, like product assembly, production planning, etc. The ultimate objective of this work is to standardize the DIM into a reference model that will be acknowledged and agreed upon by the sustainable manufacturing community

The effects of cross-functional integration mechanisms and customer characteristics on the outcomes of new product development projects

University of Technology Sydney. Faculty of Business.Over the past numbers of years, the important role of new product development (NPD) has been acknowledged by both academics and practitioners. NPD is not only a crucial means for the survival and renewal of organizations, but also a valuable source of competitive advantage and prosperity of firms. New products have been found to account for up to 50% of sales and 50% of profits of firms. Firms, however, have to confront the high failure rates of new products, which range from 40% to 50%. The importance of NPD, coupled with the poor performance of new products, motivates us to look for the drivers of new product success. The literature suggests that cross-functional integration mechanisms and customer involvement in NPD projects are crucial for new product success. Nonetheless, there is lack of research on the direct impact of cross-functional integration mechanisms and customer characteristics on NPD performance. Therefore, we aim to identify which cross-functional integration mechanisms and which customer characteristics directly affect NPD outcomes. To this end, based upon the information processing perspective and resource dependence theory, we proposed a conceptual model and developed hypotheses of the relationships between cross-functional integration mechanisms, customer characteristics, and NPD outcomes. Data was collected from marketing managers, sales managers, product managers, brand managers, and the like who have been working in Australian firms and have been involved in NPD projects. The hypotheses were tested by employing variance-based structural equation modeling (PLS-SEM). We find that five mechanisms, namely co-location, superordinate goals, the use of information and communication technology, cross-functional training, and joint reward systems have a positive impact on NPD outcomes (i.e. NPD speed, new product advantage, and new product success), whilst three other mechanisms, namely job rotation, the use of cross-functional teams, and informal coordination do not. Concerning the customer side, customers with product expertise, customers with lead user characteristics, and financially attractive customers can help firms enhance NPD speed, new product advantage, and new product success. Nevertheless, innovative customers and customers with price expertise have no influence on these three NPD outcomes. Our study adds to the limited research on the direct effects of cross-functional integration mechanisms and customer characteristics on NPD outcomes, and provides a more comprehensive picture of the factors driving NPD performance than existing studies in the research stream. Our findings also enable firms to select the effective integration mechanisms as well as the right customers for NPD projects, thereby maximizing the success of new products

Body Part Surrogates for Medicine, Comfort and Safety Applications

Body part surrogates made with support from additive manufacturing (AM) technologies belong to a rapidly developing area of modeling. Although computer-based and mathematical modeling of complex processes is already an established field, these are not free from inherited problems. Surrogate modeling (physical modeling) being a subject of its own successfully complement mathematical and computer modeling and helps to cross-validate these methods and improve particular models. Present chapter provides a discussion on the general aspects of modeling relevant to the design, manufacturing and application of body part surrogates It also introduces new term ‘surrogate twins’ using the analogy of ‘virtual twins’. It also outlines a number of known applications of body part surrogates manufactured with support of AM in medicine, safety and comfort research. Strong and weak points of particular surrogate models is discussed basing on the general concepts of modeling including defining of particular surrogate model purposes, approximations, the ways of model validation, input parameter harvesting, related measurement systems and data processing, and setups for material and product testing. Comprehensive references will allow readers getting detailed information regarding discussed issues

The interaction of lean and building information modeling in construction

Lean construction and Building Information Modeling are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, fifty-six interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete, but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers and developers of IT systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies

Comprehensive Information Integration Modeling Framework for Video Titling

In e-commerce, consumer-generated videos, which in general deliver consumers' individual preferences for the different aspects of certain products, are massive in volume. To recommend these videos to potential consumers more effectively, diverse and catchy video titles are critical. However, consumer-generated videos seldom accompany appropriate titles. To bridge this gap, we integrate comprehensive sources of information, including the content of consumer-generated videos, the narrative comment sentences supplied by consumers, and the product attributes, in an end-to-end modeling framework. Although automatic video titling is very useful and demanding, it is much less addressed than video captioning. The latter focuses on generating sentences that describe videos as a whole while our task requires the product-aware multi-grained video analysis. To tackle this issue, the proposed method consists of two processes, i.e., granular-level interaction modeling and abstraction-level story-line summarization. Specifically, the granular-level interaction modeling first utilizes temporal-spatial landmark cues, descriptive words, and abstractive attributes to builds three individual graphs and recognizes the intra-actions in each graph through Graph Neural Networks (GNN). Then the global-local aggregation module is proposed to model inter-actions across graphs and aggregate heterogeneous graphs into a holistic graph representation. The abstraction-level story-line summarization further considers both frame-level video features and the holistic graph to utilize the interactions between products and backgrounds, and generate the story-line topic of the video. We collect a large-scale dataset accordingly from real-world data in Taobao, a world-leading e-commerce platform, and will make the desensitized version publicly available to nourish further development of the research community...Comment: 11 pages, 6 figures, to appear in KDD 2020 proceeding

Identification of cost-effective pavement management systems strategies a reliable tool to enhance pavement management implementations

Modeling asset deterioration is a key business process within Transportation Asset Management. Road agencies should budget a large amount of public money to reduce the number of accidents and achieve a high level of service of the road system. Managing and preserving those investments is crucial, even more in the actual panorama of limiting funding. Therefore, roadway agencies have to increase their efforts on monitoring pavement networks and implementing data processing tools to promote cost-effective Pavement Management System (PMS) strategies. A comprehensive PMS database, in fact, ensures reliable decisions based on survey data and sets rules and procedures to analyze data systematically. However, the development of adequate pavement deterioration prediction models has proven to be difficult, because of the high variability and uncertainty in data collection and interpretation, and because of the large quantity of data information from a wide variety of sources to be processed. This research proposes a comprehensive methodology to design and implement pavement management strategies at the network level, based on road agency local conditions. Such methodology includes the identification of suitable indexes for the pavement condition assessment, the design of strategies to collect pavement data for the agency maintenance systems, the development of data quality and data cleansing criteria to support data processing and, at last, the implementation spatial location procedures to integrate pavement data involved in the comprehensive PMS. This work develops network-level pavement deterioration models, and reviews road agency preservation policies, to evaluate the effectiveness of maintenance treatment, which is essential for a cost-effective PMS. It is expected that the resulting methodology and the developed applications, product of this research, will constitute a reliable tool to support agencies in their effort to implement their PMS