scholarly journals DEVELOPING A FRAMEWORK TO EVALUATE INDIVIDUAL LEARNING IN ENGINEERING DESIGN PROBLEMS – PART 1: TEACHING THROUGH SIMULACRA OF REAL-WORLD PROBLEMS

2019 ◽  
Author(s):  
Nishant Balakrishnan
Keyword(s):  
Engineering Design ◽  
Real World ◽  
Problem Based Learning ◽  
Design Problems ◽  
Design Engineers ◽  
Engineering Design Problems ◽  
University Of Manitoba ◽  
The University ◽  
Selection Of ◽  
Real World Problems

In the context of teaching design, engineers often have a strong preference for problem-based learning because the skills they are trying to teach are intrinsic to the solving of design problems. The proliferation of problem-based learning (PBL) in capstone and now cornerstone engineering design courses is well supported by industry and faculty and the trend has been towards seeing more PBL in engineering design courses. This paper explores the basic selection of engineering design problems and presents a fairly simple dilemma: the skills that are required to solve a problem are not necessarily the skills that are taught by the problem if the problem is truly open-ended. This paper presents the idea of using engineering problems that are carefully constructed simulacra of real-world problems with built in scaffolding to create PBL experiences for students that are educationally complete and meaningful. This paper presents examples from two courses developed at the University of Manitoba based on this approach, outcomes of and responses to the course layout, and ideas for how this model can be extended to other courses or programs.

Tiki-taka algorithm: a novel metaheuristic inspired by football playing style

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohd Fadzil Faisae Ab. Rashid
Keyword(s):  
Engineering Design ◽  
Real World ◽  
Design Methodology ◽  
Benchmark Problems ◽  
Design Problems ◽  
System Complexity ◽  
Content Type ◽  
Engineering Design Problems ◽  
Real World Problems ◽  
Highly Cited

Purpose Metaheuristic algorithms have been commonly used as an optimisation tool in various fields. However, optimisation of real-world problems has become increasingly challenging with to increase in system complexity. This situation has become a pull factor to introduce an efficient metaheuristic. This study aims to propose a novel sport-inspired algorithm based on a football playing style called tiki-taka. Design/methodology/approach The tiki-taka football style is characterised by short passing, player positioning and maintaining possession. This style aims to dominate the ball possession and defeat opponents using its tactical superiority. The proposed tiki-taka algorithm (TTA) simulates the short passing and player positioning behaviour for optimisation. The algorithm was tested using 19 benchmark functions and five engineering design problems. The performance of the proposed algorithm was compared with 11 other metaheuristics from sport-based, highly cited and recent algorithms. Findings The results showed that the TTA is extremely competitive, ranking first and second on 84% of benchmark problems. The proposed algorithm performs best in two engineering design problems and ranks second in the three remaining problems. Originality/value The originality of the proposed algorithm is the short passing strategy that exploits a nearby player to move to a better position.

scholarly journals Multipopulation Ensemble Particle Swarm Optimizer for Engineering Design Problems

2020 ◽  
Vol 2020 ◽  
pp. 1-30
Author(s):  
Ziang Liu ◽  
Tatsushi Nishi
Keyword(s):  
Engineering Design ◽  
Real World ◽  
Particle Swarm ◽  
Engineering Problem ◽  
Particle Swarm Optimizer ◽  
Design Problems ◽  
Source Codes ◽  
Searching Strategy ◽  
Engineering Design Problems ◽  
Improved Function

Particle swarm optimization (PSO) is an efficient optimization algorithm and has been applied to solve various real-world problems. However, the performance of PSO on a specific problem highly depends on the velocity updating strategy. For a real-world engineering problem, the function landscapes are usually very complex and problem-specific knowledge is sometimes unavailable. To respond to this challenge, we propose a multipopulation ensemble particle swarm optimizer (MPEPSO). The proposed algorithm consists of three existing efficient and simple PSO searching strategies. The particles are divided into four subpopulations including three indicator subpopulations and one reward subpopulation. Particles in the three indicator subpopulations update their velocities by different strategies. During every learning period, the improved function values of the three strategies are recorded. At the end of a learning period, the reward subpopulation is allocated to the best-performed strategy. Therefore, the appropriate PSO searching strategy can have more computational expense. The performance of MPEPSO is evaluated by the CEC 2014 test suite and compared with six other efficient PSO variants. These results suggest that MPEPSO ranks the first among these algorithms. Moreover, MPEPSO is applied to solve four engineering design problems. The results show the advantages of MPEPSO. The MATLAB source codes of MPEPSO are available at https://github.com/zi-ang-liu/MPEPSO.

scholarly journals SRIFA: Stochastic Ranking with Improved-Firefly-Algorithm for Constrained Optimization Engineering Design Problems

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 250 ◽  
Author(s):  
Umesh Balande ◽  
Deepti Shrimankar
Keyword(s):  
Constrained Optimization ◽  
Engineering Design ◽  
Real World ◽  
Optimization Design ◽  
Firefly Algorithm ◽  
Optimization Problems ◽  
Design Problems ◽  
Improved Firefly Algorithm ◽  
Engineering Design Problems ◽  
And Performance

Firefly-Algorithm (FA) is an eminent nature-inspired swarm-based technique for solving numerous real world global optimization problems. This paper presents an overview of the constraint handling techniques. It also includes a hybrid algorithm, namely the Stochastic Ranking with Improved Firefly Algorithm (SRIFA) for solving constrained real-world engineering optimization problems. The stochastic ranking approach is broadly used to maintain balance between penalty and fitness functions. FA is extensively used due to its faster convergence than other metaheuristic algorithms. The basic FA is modified by incorporating opposite-based learning and random-scale factor to improve the diversity and performance. Furthermore, SRIFA uses feasibility based rules to maintain balance between penalty and objective functions. SRIFA is experimented to optimize 24 CEC 2006 standard functions and five well-known engineering constrained-optimization design problems from the literature to evaluate and analyze the effectiveness of SRIFA. It can be seen that the overall computational results of SRIFA are better than those of the basic FA. Statistical outcomes of the SRIFA are significantly superior compared to the other evolutionary algorithms and engineering design problems in its performance, quality and efficiency.

scholarly journals EVALUATING STUDENT DESIGN ACTIVITY IN ENGINEERING DESIGN PROJECTS

2011 ◽  
Author(s):  
D. S. Petkau ◽  
D. D. Mann
Keyword(s):  
Engineering Design ◽  
Evaluation Process ◽  
Design Activity ◽  
Design Teams ◽  
Short Term ◽  
Design Problems ◽  
Design Activities ◽  
University Of Manitoba ◽  
Design Projects ◽  
The University

Student design projects in engineering courses are usually short term conceptual design problems. Upon completion of the projects it is difficult to assess which design activities had the greatest contribution to the success of the design. In the fall of 2006, students in 2nd, 3rd, and 4th year Design Trilogy courses at the University of Manitoba were asked to keep extensive design journals. Design teams consisted of multiyear students completing various industry projects. Student design activities recorded in the journals were coded. Data were compared between design teams and between students in the different years of study. This paper describes the evaluation process and reports on the preliminary findings.

scholarly journals Recent Enhancements to the Biosystems Engineering Design Trilogy at the University of Manitoba

2012 ◽  
Author(s):  
Danny D Mann ◽  
Kris J Dick ◽  
Sandra A Ingram
Keyword(s):  
Engineering Design ◽  
Engineering Students ◽  
Course Design ◽  
Professional Communication ◽  
First Year ◽  
Design Problems ◽  
Capstone Course ◽  
University Of Manitoba ◽  
Second Year ◽  
The University

In previous years, several improvements to the teaching of engineering design were made by staff in the Department of Biosystems Engineering at The University of Manitoba. The first innovation occurred when a trilogy of courses spanning the final three years of the program was introduced as a replacement for a single capstone course in the final year of the program. In its original conception, engineering students were to get three opportunities to be involved in design problems originating from industry, with greater expectations with each subsequent experience. A second innovation occurred when technical communication was formally integrated within the trilogy of design courses. This innovation has helped engineering students realize the value of professional communication skills in collaborating with each other and in preparing reports and presentations for an industry client. A third innovation occurred three years ago when the decision was made to allow students to participate in the prototyping of their designs. The so-called “Design Trilogy” now consists of a single course (Design Trilogy I) taken during the second year of the engineering program (which builds upon the first-year design experience with the requirement of a conceptual solution in response to a design problem provided by industry) and two courses taken during the final year of the program. Students are required to have a design completed on paper by the completion of Design Trilogy II and fabrication of the prototype occurs during Design Trilogy III. The student experience in the Design Trilogy, with particular emphasis on curriculum innovations in Design Trilogy III, will be discussed.

scholarly journals DEVELOPING A FRAMEWORK TO EVALUATE INDIVIDUAL LEARNING IN ENGINEERING DESIGN PROBLEMS – PART 2: ASSESSMENT OF INDIVIDUAL LEARNING IN TEAM ENVIRONMENTS

2019 ◽  
Author(s):  
Nishant Balakrishnan
Keyword(s):  
Learning Outcomes ◽  
Individual Learning ◽  
Careful Consideration ◽  
Engineering Practice ◽  
Design Problems ◽  
Engineering Design Problems ◽  
University Of Manitoba ◽  
And Performance ◽  
Set Up ◽  
The University

Engineers often model their teaching based on how they expect students to function once they graduate, and as a result they typically have a strong affinity for Problem-Based Learning (PBL) and Team-Based Learning (TBL) approaches. In many cases, this works quite well and has been proven to increase student engagement and performance of design teams. At the same time, as more of the curriculum relies on group projects, there is a simple dilemma that is created: how do you ensure that the learning outcomes a team demonstrates are accurate reflections of what each individual in the team is learning? This rarely poses a challenge in engineering practice, as engineers are expected to specialize, but in an outcome-based accreditation, this can become a serious issue if there isn’t a careful consideration of this in the structure of TBL courses. This paper explores the application of an evaluative framework to a course with strong PBL and TBL components that is set up to ensure that students are not only exposed to all learning outcomes as they tackle a project, but are individually evaluated on their ability to show competence in these outcomes. The prime methodology of this framework is an evaluative tool called an "open-ended design exam" that uses a 1:1 mapping of team and individual learning, with scaffolding in the course frameworks to support this. This paper presents application of this approach to two courses developed at the University of Manitoba, outcomes and responses to the course layout, and suggestions for extensions to other courses or programs.

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.

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.

Sign in / Sign up

Export Citation Format

Share Document