Assembly and Disassembly Planning by using Fuzzy Logic & Genetic Algorithms

The authors propose the implementation of hybrid Fuzzy Logic-Genetic Algorithm (FL-GA) methodology to plan the automatic assembly and disassembly sequence of products. The GA-Fuzzy Logic approach is implemented onto two levels. The first level of hybridization consists of the development of a Fuzzy controller for the parameters of an assembly or disassembly planner based on GAs. This controller acts on mutation probability and crossover rate in order to adapt their values dynamically while the algorithm runs. The second level consists of the identification of theoptimal assembly or disassembly sequence by a Fuzzy function, in order to obtain a closer control of the technological knowledge of the assembly/disassembly process. Two case studies were analyzed in order to test the efficiency of the Fuzzy-GA methodologies

A Simulation-Based Analysis of the Impact of In-Sourcing a Major Process Element on the Coast Guard HH-601 Depot Maintenance Process

Leaders at the United States Coast Guard\u27s Aircraft Repair and Service Center (ARSC) in Elizabeth City, North Carolina recently formalized their planning and analysis functions by adding a dedicated branch to their command structure. The Planning and Analysis Branch intends to apply computer modeling and simulation to study the impact of process changes to the various Programmed Depot Maintenance (PDM) lines. This research considers the applicability of this type of modeling and simulation, using ARENA to study the current HH-6OJ PDM process. The contribution of this research is a methodology specific to ARSC needs, an analysis of methodology based on a discrete event simulation model of PDM lines, and a specific case study demonstrating the methodologies. The response variable of interest is average PDM process time as a function of either in-sourcing or out-sourcing labor for a major process step. The research includes development and evaluation of a macro-level process model using ARENA 5.0

Design Concepts for Automating Maintenance Instructions

This research task was performed under the Technology for Readiness and Sustainment (TRS) contract (F33615-99-D-6001) for the Air Force Research Laboratory (AFRL), Sustainment Logistics Branch (HESS) at Wright-Patterson AFB, OH. The period of performance spanned one year starting 29 January 1999. The objective of this task was to develop and demonstrate a framework that can support the automated validation and verification of aircraft maintenance Technical Orders (TOs). The research team examined all stages ofTO generation to determine which tasks most warranted further research. From that investigation, validation and verification of appropriate, safe, and correct procedure steps emerged as the primary research target. This process would be based on available computer-aided design (CAD) data, procedure step ordering from existing sources, and human models. This determination was based on which tasks could yield the greatest impact on the authoring process and offer the greatest potential economic benefits. The team then developed a research roadmap and outlined specific technologies to be addressed in possible subsequent Air Force research tasks. To focus on the potential technology integration of the validation and verification component into existing or future TO generation procedures, we defined a demonstration scenario. Using the Front Uplock Hook assembly from an F/A-18 as the subject, we examined task procedure steps and failures that could be exposed by automated validation tools. These included hazards to personnel, damage to equipment, and incorrect disassembly order. Using the Parameterized Action Representation (PAR) developed on previous projects for actions and equipment behaviors, we characterized procedure steps and their positive and negative consequences. Finally, we illustrated a hypothetical user interface extension to a typical Interactive Electronic Technical Manual (IETM) authoring system to demonstrate how this process might appear to the TO author

Task planning with uncertainty for robotic systems

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated

A conditional CRISPR/Cas9 system gives novel insights into actin dynamics in Toxoplasma gondii

Actin is a highly abundant structural protein in eukaryotes that is critical for several cellular processes. In the apicomplexan parasite Toxoplasma gondii, actin is critical for the completion of the lytic cycle and, thus, parasite survival. Only recently, actin structures were visualised in Toxoplasma by exploiting actin-chromobodies, revealing an extensive actin network within the parasitophorous vacuole (PV) (Periz et al. 2017). This network consists of intravacuolar filamentous structures that connect individual parasites within the PV. In addition, parasites possess a cytosolic actin centre (cAC) anterior to the nucleus. The study presented here aimed at exploiting actin visualisation to investigate actin dynamics in unprecedented detail in vivo. For this purpose, I established a conditional CRISPR/Cas9 that allows for rapid and efficient gene disruption in Toxoplasma. Combining this system with the actin-chromobody technology granted detailed insights into the actin dynamics in intracellular parasites. I identified the actin depolymerisation factor (TgADF) as an important factor in the disassembly of the intravacuolar F-actin filaments prior to parasite egress from the host cell. Furthermore, this study revealed TgFormin2 to be critical for maintaining the cAC. Since cAC loss severely impaired actin distribution and peripheral actin flow in intracellular parasites, I concluded that TgFormin2 represents a major key player in mediating proper actin dynamics. TgFormin2 also appeared to be important for apicoplast inheritance and positioning. In summary, data presented in this thesis significantly contribute to the understanding of actin dynamics in Toxoplasma. Further insights into apicomplexan actin dynamics will be gained by exploiting the conditional CRISPR/Cas9 technology for phenotypic screening approaches

A review of the state of the art in tools and techniques used to evaluate remanufacturing feasibility

Remanufacturing often seems a sensible approach for companies looking to adopt sustainable business plans to achieve long term success. However, remanufacturing must not be treated as a panacea for achieving a sustainable business, as issues such as market demand, product design, end of life condition and information uncertainty can affect the success of a remanufacturing endeavour. Businesses therefore need to carefully assess the feasibility of adopting remanufacturing before committing to a particular activity or strategy. To aid this decision process, a number of tools and techniques have been published by academics. However, there is currently not a formal review and comparison of these tools and how they relate to the decision process. The main research objective of this study has therefore been to identify tools and methods which have been developed within academia to support the decision process of assessing and evaluating the viability of conducting remanufacturing, and evaluate how they have met the requirements of the decision stage. This has been achieved by conducting a content analysis. Three bibliographic databases were searched (Compendex, Web of Science and Scopus) using a structured keyword search to identify relevant literature. The identified tools were then split into 6 categories based upon the specific decision stages and applications, then evaluated against a set of key criteria which are, the decision factors (economic, environmental, social) and the inclusion of uncertainty. The key finding of this study has been that although decision factors are generally well covered, operational tools and the use of uncertainty are often neglected