Conceptual Design of Electromechanical Actuation Systems for Large-Sized Directional Control Valves

Increasing performance in modern hydraulics is achieved by a close investigation of possible enhancements of its components. Prior research has pointed out that electromechanical actuators can form suitable alternatives to hydraulically piloted control systems. Since the requirements at these actuation systems depend on the operating conditions of the system, each actuator can be optimized to the respective hydraulic system. Considering that many different conceptual designs are suitable, the phase of conceptual design plays a decisive role during the design process. Therefore, this paper focuses on the process of developing new conceptual designs for electromechanical valve actuation systems using the method of function structures. Aiming to identify special design features, which need to be considered during the design process of electromechanical actuation systems, an exemplary actuator was designed based on the derived function structure. To highlight the potential of function structures for the development of new electromechanical valve actuation systems, two principal concepts, which allow the reduction of the necessary forces, have been developed by extending the function structure. These concepts have been experimentally investigated to identify their advantages and disadvantages.

Students’ ability to correctly apply differentiation rules to structurally different functions

The derivative concept is studied in first-year university mathematics. In this study, we focused on students’ ability to correctly apply the rules for derivatives of functions with the different structures that they encounter in their university studies. This was done by investigating the online responses of first-year students at the University of KwaZulu-Natal to online quizzes that contributed to their assessment. Based on this investigation, we then interviewed eight students to gain an insight into the thinking behind their responses. We report on the analysis of students’ responses to five items on the online quizzes based on the derivative concept. The categories in which those items were based are: condition for existence of derivative at a point; rules for derivatives of standard functions; application of chain rule to different function structures; the application of multiple rules; and application of derivatives to optimise a function. Our findings indicate that students had difficulty in detecting that multiple rules for derivatives were required to differentiate certain types of functions represented in symbolic form. Furthermore, students had difficulty in finding the derivative of a function when more than one application of the chain rule was required. However, there were students who had the ability to apply the rules for derivatives of functions without difficulty. In particular, most of the students were able to correctly recall the differentiation rules for functions with standard structures f(x)=xn, h(x)=ekx and y=[g(x)]n, n 0 and k is a non-zero constant. Students were also able to correctly apply the chain rule to an exponential function with base e, raised to 4x. The majority of students were able to correctly apply the chain rule together with differentiation rules for logarithmic and exponential (with bases a >1) function structures, and function structures that required the application of the product rule together with the chain rule. Most of the students were able to apply derivatives to optimise a function. Significance: A significant percentage of students who took online quizzes experienced difficulties with applying multiple differentiation rules in the context of a single function. The difficulties stemmed from their inability to detect from the structure of the function which rules should be applied and also the order in which those relevant rules should be applied.

A Statistical Approach to Ranking Similarities of Three Function Structure Groups Using Directed Graphs

Prior efforts in the study of engineering design employed various approaches to decompose product design. Design engineers use functional representation, and more precisely function structures, to define a product’s functionality. However, significant barriers remain to objectively quantifying the similarity between two function structures, even for the same product when developed by multiple designers. For function-structure databases this means that function-structures are implicitly categorized leaving the possibility of incorrect categorization and reducing efficacy of returned analogous correlations. Improvements to efficacy in database organization and queries are possible by objectively quantifying the similarity between function structures. The proposed method exploits fundamental properties of function-structures and design taxonomies. We convert function-structures into directed graphs (digraphs) and equivalent adjacency matrices. The conversion maintains the directed (function → flow → function) progression inherent to function-structures and enables the transformation of the function-structure into a standardized graph. For design taxonomies (e.g. D-APPS), graph nodes represent flows in a consistent (but arbitrary) ordering. By exploiting the directional properties of function-structures and defining the flows as the graphical nodes, the objective and standardized comparison of two function-structures becomes feasible. We statistically quantify the association between digraphs using the Pearson Product Moment Correlation (PPMC) for both within-group and between-group comparisons. The method was tested on three product types (ball thrower, food processor, and an ice cream maker) with function-structures defined by various designers. The method suggested herein is provided as a proof-of-concept with suggested verification and validation approaches for further development.

Introduction to quantitative engineering design methods via controls engineering

Functional modeling is an effective method of depicting products in the design process. Using this approach, product architecture, concept generation, and physical modeling all contribute to the design process to generate a result full of quality and functionality. The functional basis approach provides taxonomy of uniform vocabulary to produce function structures with consistent functions (verbs) and flows (nouns). Material and energy flows dominate function structures in the mechanical engineering domain with only a small percentage including signal flows. Research suggests that the signal flow gap is due to the requirement of “carrier” flows of either material or energy to transport the signals between functions. This research suggests that incorporating controls engineering methodologies may increase the number of signal flows in function structures. We show correlations between the functional modeling and controls engineering in four facets: schematic similarities, performance matching through flows, mathematical function creation using bond graphs, and isomorphic matching of the aforementioned characteristics allows for analogical solutions. Controls systems use block diagrams to represent the sequential steps of the system. These block diagrams parallel the function structures of engineering design. Performance metrics between the two domains can be complimentary when decomposed down to nondimensional engineering units. Mathematical functions of the actions in controls systems can resemble the functional basis functions with bond graphs by identifying characteristic behavior of the functions on the flows. Isomorphic matching, using the schematic diagrams, produces analogies based upon similar functionality and target performance metrics. These four similarities bridge the mechanical and electrical domains via the controls domain. We provide concepts and contextualization for the methodology using domain-agnostic examples. We conclude with suggestion of pathways forward for this preliminary research.

Comparing function structures and pruned function structures for market price prediction: An approach to benchmarking representation inferencing value

Benchmarking function modeling and representation approaches requires a direct comparison, including the inferencing support by the different approaches. To this end, this paper explores the value of a representation by comparing the ability of a representation to support reasoning based on varying amounts of information stored in the representational components of a function structure: vocabulary, grammar, and topology. This is done by classifying the previously developed functional pruning rules into vocabulary, grammatical, and topological classes and applying them to function structures available from an external design repository. The original and pruned function structures of electromechanical devices are then evaluated for how accurately market values can be predicted using the graph complexity connectivity method. The accuracy is found to be inversely related to the amount of information and level of detail. Applying the topological rule does not significantly impact the predictive power of the models, while applying the vocabulary rules and the grammar rules reduces the accuracy of the predictions. Finally, the least predictive model set is that which had all rules applied. In this manner, the value of a representation to predict or answer questions is quantified.

The integrated function modeling framework and its relation to function structures

Research and industrial practice have produced a host of function models and modeling approaches over the last decades. Each of these is meant to support designers in their design endeavors. Industrial practice is excessively diversified in terms of contextual requirements, aims, and adopted processes; this automatically begs the question which of the existing models should be selected for application in a specific situation. This paper sets out to contribute to this discourse. It strives to benchmark the fairly novel integrated function modeling (IFM) framework against the well-established function structures modeling approach. The paper comparatively investigates the respective capabilities of the approaches, following the benchmarking protocol used earlier in relation to this Special Issue. Function structures are used as reference as they represent one of the most widespread function modeling approaches in research and practice. Both function structures and the IFM framework are exemplarily applied for modeling a glue gun. The gradual generation and refinement of the models is used to showcase their respective benefits and shortcomings. Eventually, the IFM framework is found to excel over function structures in terms of comprehensiveness and support for different types of function analyses. Finally, future research directions are proposed.