Incorporating Social Product Development in Distributed Collaborative Design Education

2013 ◽  
Author(s):  
Dazhong Wu ◽  
Merlin Morlock ◽  
Prateek Pande ◽  
David W. Rosen ◽  
Dirk Schaefer
Keyword(s):  
Product Development ◽  
Engineering Design ◽  
Social Networking Sites ◽  
Collaborative Design ◽  
Design Education ◽  
Design Problems ◽  
Mass Collaboration ◽  
Engineering Design Problems ◽  
Social Product ◽  
Product Realization

Over the past few years, Social Product Development (SPD) has emerged as a new trend to improve traditional engineering design and product realization processes. SPD involves the concepts of crowdsourcing, mass collaboration, customer co-creation, and most recently cloud-based design and manufacturing. One of the key characteristics of SPD is to apply social computing techniques (e.g., social networking sites and online communities) to support different phases of product realization processes. In line with this trend, our objective is to help our students become familiar with this paradigm shift and learn how to solve engineering design problems in a distributed and collaborative setting. Consequently, we have experimented with introducing some aspects of SPD into one of our graduate level engineering design courses. In this paper, we (1) introduce a SPD process that is implemented in the course, (2) present a case study from one of the design teams, and (3) share our experience and lessons with respect to the implementation of the SPD process.

Introducing the Industrial Product Realization Process Into Mechanical Engineering Design Education

1995 ◽  
Author(s):  
Vance D. Browne
Keyword(s):  
Product Development ◽  
Engineering Design ◽  
Design Education ◽  
Process Development ◽  
Project Planning ◽  
Concept Generation ◽  
Engineering Project ◽  
Engineering Design Education ◽  
Realization Process ◽  
Product Realization

Abstract The process by which new products are brought to market — the product realization process, or PRP — can be introduced in engineering design education. In industry, the PRP has been evolving to concurrent engineering and product teams. The PRP includes components such as concept generation, analysis, manufacturing process development and customer interaction. Also, it involves the sequencing of the components and their connections which includes teamwork, project planning, meetings, reports and presentations. A capstone senior engineering project, along with classroom lectures and presentations can be structured to provide knowledge and experience to the students in many of the PRP components and the connections. This paper will give an overview of the PRP and a project/lecture structure at the author’s university. The instructor recently joined the academic ranks after years in industry with responsibility for directing product development and R&D and for leading product development teams.

Standards, Codes of Practice and Expert Systems

1988 ◽  
Vol 21 (1) ◽  
pp. 5-9 ◽  
Author(s):  
E G McCluskey ◽  
S Thompson ◽  
D M G McSherry
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Engineering Design ◽  
Performance Criteria ◽  
Design Problems ◽  
Codes Of Practice ◽  
Engineering Design Problems ◽  
And Performance

Many engineering design problems require reference to standards or codes of practice to ensure that acceptable safety and performance criteria are met. Extracting relevant data from such documents can, however, be a problem for the unfamiliar user. The use of expert systems to guide the retrieval of information from standards and codes of practice is proposed as a means of alleviating this problem. Following a brief introduction to expert system techniques, a tool developed by the authors for building expert system guides to standards and codes of practice is described. The steps involved in encoding the knowledge contained in an arbitrarily chosen standard are illustrated. Finally, a typical consultation illustrates the use of the expert system guide to the standard.

Training the Participatory Renaissance Man: Past Creative Experiences and Collaborative Design

2013 ◽  
Author(s):  
Jonathan Sauder ◽  
Yan Jin
Keyword(s):  
Engineering Design ◽  
Collaborative Design ◽  
Design Education ◽  
Protocol Analysis ◽  
Creative Cognition ◽  
Collaborative Environment ◽  
Engineering Design Education ◽  
Renaissance Man ◽  
Current Engineering ◽  
And Training

Students are frequently trained in a variety of methodologies to promote their creativity in the collaborative environment. Some of the training and methods work well, while others present challenges. A collaborative stimulation approach is taken to extend creative cognition to collaborative creativity, providing new insights into design methodologies and training. An experiment using retrospective protocol analysis, originally conducted to identify the various types of collaborative stimulation, revealed how diversity of past creative experiences correlates with collaborative stimulation. This finding aligns with previous research. Unfortunately, many current engineering design education programs do not adequately provide opportunities for diverse creative experiences. As this study and other research has found, there is a need to create courses in engineering design programs which encourage participation in diverse creative activities.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

scholarly journals Lévy-Flight Moth-Flame Algorithm for Function Optimization and Engineering Design Problems

2016 ◽  
Vol 2016 ◽  
pp. 1-22 ◽  
Author(s):  
Zhiming Li ◽  
Yongquan Zhou ◽  
Sen Zhang ◽  
Junmin Song
Keyword(s):  
Engineering Design ◽  
Function Optimization ◽  
Superior Performance ◽  
Local Optimum ◽  
Lévy Flight ◽  
Design Problems ◽  
Levy Flight ◽  
Spiral Path ◽  
Straight Line ◽  
Engineering Design Problems

The moth-flame optimization (MFO) algorithm is a novel nature-inspired heuristic paradigm. The main inspiration of this algorithm is the navigation method of moths in nature called transverse orientation. Moths fly in night by maintaining a fixed angle with respect to the moon, a very effective mechanism for travelling in a straight line for long distances. However, these fancy insects are trapped in a spiral path around artificial lights. Aiming at the phenomenon that MFO algorithm has slow convergence and low precision, an improved version of MFO algorithm based on Lévy-flight strategy, which is named as LMFO, is proposed. Lévy-flight can increase the diversity of the population against premature convergence and make the algorithm jump out of local optimum more effectively. This approach is helpful to obtain a better trade-off between exploration and exploitation ability of MFO, thus, which can make LMFO faster and more robust than MFO. And a comparison with ABC, BA, GGSA, DA, PSOGSA, and MFO on 19 unconstrained benchmark functions and 2 constrained engineering design problems is tested. These results demonstrate the superior performance of LMFO.

scholarly journals Performance Comparison of Recent Population-Based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 341
Author(s):  
Bugra Alkan ◽  
Malarvizhi Kaniappan Chinnathai
Keyword(s):  
Engineering Design ◽  
Mechanical Design ◽  
Search Algorithm ◽  
Computation Time ◽  
Population Based ◽  
Performance Comparison ◽  
Design Problems ◽  
Component Design ◽  
Engineering Design Problems ◽  
Optimisation Algorithms

The optimisation of complex engineering design problems is highly challenging due to the consideration of various design variables. To obtain acceptable near-optimal solutions within reasonable computation time, metaheuristics can be employed for such problems. However, a plethora of novel metaheuristic algorithms are developed and constantly improved and hence it is important to evaluate the applicability of the novel optimisation strategies and compare their performance using real-world engineering design problems. Therefore, in this paper, eight recent population-based metaheuristic optimisation algorithms—African Vultures Optimisation Algorithm (AVOA), Crystal Structure Algorithm (CryStAl), Human-Behaviour Based Optimisation (HBBO), Gradient-Based Optimiser (GBO), Gorilla Troops Optimiser (GTO), Runge–Kutta optimiser (RUN), Social Network Search (SNS) and Sparrow Search Algorithm (SSA)—are applied to five different mechanical component design problems and their performance on such problems are compared. The results show that the SNS algorithm is consistent, robust and provides better quality solutions at a relatively fast computation time for the considered design problems. GTO and GBO also show comparable performance across the considered problems and AVOA is the most efficient in terms of computation time.

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