Computer Aided Design of Side Actions for Injection Molding of Complex Parts

Often complex molded parts include undercuts, patches on the part boundaries that are not accessible along the main mold opening directions. Undercuts are molded by incorporating side actions in the molds. Side actions are mold pieces that are removed from the part using translation directions different than the main mold opening direction. However, side actions contribute to mold cost by resulting in an additional manufacturing and assembly cost as well as by increasing the molding cycle time. Therefore, generating shapes of side actions requires solving a complex geometric optimization problem. Different objective functions may be needed depending upon different molding scenarios (e.g., prototyping versus large production runs). Manually designing side actions is a challenging task and requires considerable expertise. Automated design of side actions will significantly reduce mold design lead times. This thesis describes algorithms for generating shapes of side actions to minimize a customizable molding cost function. Given a set of undercut facets on a polyhedral part and the main parting direction, the approach works in the following manner. First, candidate retraction space is computed for every undercut facet. This space represents the candidate set of translation vectors that can be used by the side action to completely disengage from the undercut facet. As the next step, a discrete set of feasible, non-dominated retractions is generated. Then the undercut facets are grouped into undercut regions by performing state space search over such retractions. This search step is performed by minimizing the customizable molding cost function. After identifying the undercut regions that can share a side action, the shapes of individual side actions are computed. The approach presented in this work leads to practically an optimal solution if every connected undercut region on the part requires three or fewer side actions. Results of computational experiments that have been conducted to assess the performance of the algorithms described in the thesis have also been presented. Computational results indicate that the algorithms have acceptable computational performance, are robust enough to handle complex part geometries, and are easy to implement. It is anticipated that the results shown here will provide the foundations for developing fully automated software for designing side actions in injection molding

Development of a method to study aircraft trajectory optimisation in the presence of icing conditions

There is a growing demand for new technologies and ight procedures that will enable aircraft operators to burn less fuel and reduce the impacts of aviation on the environment. Conventional approaches to trajectory optimisation do not include aircraft systems in the optimisation set-up. However, the fuel penalty due to aircraft systems operation is signi cant. Thus, applying optimised trajectories which do not account for systems o -takes in real aircraft Flight Management System (FMS) will likely fail to achieve a true optimum. This is more important in real scenarios where the ambient conditions in uence the systems operation signi cantly. This research proposed an ice protection methodology which enables the development of a decision making process within the FMS dependent on weather conditions; thus transforming the conventional anti-icing method into a more intelligent system. A case of a medium size transport aircraft ight from London - Amsterdam under various levels of possible icing was studied. The results show that fuel burn due to anti-icing operation can increase up to 3.7% between climb and cruise altitudes. Up to 5.5% of this penalty can be saved using icing optimised trajectories. A 45% reduction in awakenings due to noise was achieved with 3% fuel penalty. The novelty of the study was extended using 3D optimisation to further improve ight operations. It was found that the simulation successfully changed the lateral position of the aircraft to minimise the time spent and distance covered in icing conditions. The work here presents a feasible methodology for future intelligent ice protection system (IPS) development, which incorporates intelligent operation

In-Mold Assembly of Multi-Functional Structures

Combining the recent advances in injection moldable polymer composites with the multi-material molding techniques enable fabrication of multi-functional structures to serve multiple functions (e.g., carry load, support motion, dissipate heat, store energy). Current in-mold assembly methods, however, cannot be simply scaled to create structures with miniature features, as the process conditions and the assembly failure modes change with the feature size. This dissertation identifies and addresses the issues associated with the in-mold assembly of multi-functional structures with miniature components. First, the functional capability of embedding actuators is developed. As a part of this effort, computational modeling methods are developed to assess the functionality of the structure with respect to the material properties, process parameters and the heat source. Using these models, the effective material thermal conductivity required to dissipate the heat generated by the embedded small scale actuator is identified. Also, the influence of the fiber orientation on the heat dissipation performance is characterized. Finally, models for integrated product and process design are presented to ensure the miniature actuator survivability during embedding process. The second functional capability developed as a part of this dissertation is the in-mold assembly of multi-material structures capable of motion and load transfer, such as mechanisms with compliant hinges. The necessary hinge and link design features are identified. The shapes and orientations of these features are analyzed with respect to their functionality, mutual dependencies, and the process cost. The parametric model of the interface design is developed. This model is used to minimize both the final assembly weight and the mold complexity as the process cost measure. Also, to minimize the manufacturing waste and the risk of assembly failure due to unbalanced mold filling, the design optimization of runner systems used in multi-cavity molds for in-mold assembly is developed. The complete optimization model is characterized and formulated. The best method to solve the runner optimization problem is identified. To demonstrate the applicability of the tools developed in this dissertation towards the miniaturization of robotic devices, a case study of a novel miniature air vehicle drive mechanism is presented

A Cost Assessment of the Dayton Public Schools Vehicle Routing Problem

The routing and scheduling problem involves both constructing efficient routes to deliver goods or services to and from customers from a single depot or set of depots, as well as scheduling particular vehicles to these routes such that customers receive their goods within a specified time window. There have been several different methods developed to reduce the costs incurred in transporting goods or services (i.e. students) to customers (i.e. schools). This problem may be used to model many circumstances in logistics and public transportation. Several school districts do not utilize operations research techniques to minimize, as much as possible, the costs associated with the operation of its pupil transportation system. In contrast, Dayton Public Schools (DPS) employs the optimization software package VersaTrans to minimize its transportation expenses. However, due to the importance it has placed on customer satisfaction, DPS has ultimately been reduced to door-to-door pickups. This, combined with an open enrollment policy and higher fuel prices, has resulted in an explosion of transportation related costs. Though DPS has made many great strides to gain control of its spending, due primarily to better management, there is still much to accomplish. This thesis seeks to utilize the VersaTrans routing software available to the Dayton Public School district to construct efficient routes that are feasible under a consolidated bell schedule so that both bus usage and route times are minimized

visone - Software for the Analysis and Visualization of Social Networks

We present the software tool visone which combines graph-theoretic methods for the analysis of social networks with tailored means of visualization. Our main contribution is the design of novel graph-layout algorithms which accurately reflect computed analyses results in well-arranged drawings of the networks under consideration. Besides this, we give a detailed description of the design of the software tool and the provided analysis methods

Entropy-based Generating Markov Partitions for Complex Systems

Authors thank the Scottish University Physics Alliance (SUPA) support and NR also thanks PEDECIBA.Peer reviewedPostprintPublisher PD

A Monte-Carlo approach to tool selection for sheet metal punching and nibbling

Selecting the best set of tools to produce certain geometrical shapes/features in sheet metal punching is one of the problems that has a great effect on product development time, cost and achieved quality. The trend nowadays is, where at all possible, to limit design to the use of standard tools. Such an option makes the problem of selecting the appropriate set of tools even more complex, especially when considering that sheet metal features can have a wide range of complex shapes. Another dimension of complexity is limited tool rack capacity. Thus, an inappropriate tool selection strategy will lead to punching inefficiency and may require frequent stopping of the machine and replacing the required tools, which is a rather expensive and time consuming exercise. This work demonstrates that the problem of selecting the best set of tools is actually a process of searching an explosive decision tree. The difficulty in searching such types of decision trees is that intermediate decisions do not necessarily reflect the total cost implication of carrying out such a decision. A new approach to solve such a complex optimisation problem using the Monte Carlo Simulation Methods has been introduced in this thesis. The aim of the present work was to establish the use of Monte Carlo methods as an "assumptions or rule free" baseline or benchmark for the assessment of search strategies. A number of case studies are given, where the feasibility of Monte Carlo Simulation Methods as an efficient and viable method to optimise such a complex optimisation problem is demonstrated. The use of a Monte Carlo approach for selecting the best set of punching tools, showed an interesting point, that is, the effect of dominant "one-to-one" feature/tool matches on the efficiency of the search. This naturally led on to the need of a search methodology that will be more efficient than the application of the Monte Carlo method alone. This thesis presents some interesting speculations for a hybrid approach to tool selection to achieve a better solution than the use of the Monte Carlo method alone to achieve the optimum solution in a shorter time