Immersive Computing Technology to Investigate Tradeoffs Under Uncertainty in Disassembly Sequence Planning

The scientific and industrial communities have begun investigating the possibility of making product recovery economically viable. Disassembly sequence planning may be used to make end-of-life product take-back processes more cost effective. Much of the research involving disassembly sequence planning relies on mathematical optimization models. These models often require input data that is unavailable or can only be approximated with high uncertainty. In addition, there are few mathematical models that include consideration of the potential of product damage during disassembly operations. The emergence of Immersive Computing Technologies (ICT) enables designers to evaluate products without the need for physical prototypes. Utilizing unique 3D user interfaces, designers can investigate a multitude of potential disassembly operations without resorting to disassembly of actual products. The information obtained through immersive simulation can be used to determine the optimum disassembly sequence. The aim of this work is to apply a decision analytical approach in combination with immersive computing technology to optimize the disassembly sequence while considering trade-offs between two conflicting attributes: disassembly cost and damage estimation during disassembly operations. A wooden Burr puzzle is used as an example product test case. Immersive human computer interaction is used to determine input values for key variables in the mathematical model. The results demonstrate that the use of dynamic programming algorithms coupled with virtual disassembly simulation is an effective method for evaluating multiple attributes in disassembly sequence planning. This paper presents a decision analytical approach, combined with immersive computing techniques, to optimize the disassembly sequence. Future work will concentrate on creating better methods of estimating damage in virtual disassembly environments and using the immersive technology to further explore the feasible design space

Leveraging Virtual Reality Experiences With Mixed-Integer Nonlinear Programming Visualization of Disassembly Sequence Planning Under Uncertainty

Disassembly sequence planning at the early conceptual stage of design leads to enormous benefits including simplification of products, lower assembly and disassembly costs, and design modifications which result in increased potential profitability of end-of-life salvaging operations. However, in the early design stage, determining the best disassembly sequence is challenging. First, the required information is not readily available and very time-consuming to gather. In addition, the best solution is sometimes counterintuitive, even to those with experience and expertise in disassembly procedures. Integrating analytical models with immersive computing technology (ICT) can help designers overcome these issues. A two-stage procedure for doing so is introduced in this paper. In the first stage, a stochastic programming model together with the information obtained through immersive simulation is applied to determine the optimal disassembly sequence, while considering uncertain outcomes, such as time, cost, and the probability of causing damage. In the second stage, ICT is applied as a tool to explore alternative disassembly sequence solutions in an intuitive way. The benefit of using this procedure is to determine the best disassembly sequence, not only by solving the analytic model but also by capturing human expertise. The designer can apply the obtained results from these two stages to analyze and modify the product design. An example of a Burr puzzle is used to illustrate the application of the method

Levitation Simulator: Prototyping Ultrasonic Levitation Interfaces in Virtual Reality

We present the Levitation Simulator, a system that enables researchers and designers to iteratively develop and prototype levitation interface ideas in Virtual Reality. This includes user tests and formal experiments. We derive a model of the movement of a levitating particle in such an interface. Based on this, we develop an interactive simulation of the levitation interface in VR, which exhibits the dynamical properties of the real interface. The results of a Fitts' Law pointing study show that the Levitation Simulator enables performance, comparable to the real prototype. We developed the first two interactive games, dedicated for levitation interfaces: LeviShooter and BeadBounce, in the Levitation Simulator, and then implemented them on the real interface. Our results indicate that participants experienced similar levels of user engagement when playing the games, in the two environments. We share our Levitation Simulator as Open Source, thereby democratizing levitation research, without the need for a levitation apparatus.Comment: 12 pages, 14 figures, CHI'2

Mixed-stock analysis of Atlantic herring (Clupea harengus): a tool for identifying management units and complex migration dynamics

We developed and validated a mixed-stock analysis (MSA) method with 59 single-nucleotide polymorphisms selected from genome-wide data to assign individuals to populations in mixed-stock samples of Atlantic herring from the North and Baltic seas. We analysed 3734 herring from spawning locations and scientific catches of mixed feeding stocks to demonstrate a "one-fits-all" tool with unprecedented accuracy for monitoring spatio-temporal dynamics throughout a large geographical range with complex stock mixing. We re-analysed time-series data (2002-2021) and compared inferences about stock composition with estimates from morphological data. We show that contributions from the western Baltic spring-spawning stock complex, which is under management concern, have likely been overestimated. We also show that a genetically distinctive population of western Baltic autumn spawners, ascribed low fisheries importance, contributes non-negligible and potentially temporally increasing proportions to mixed-stock aggregations, calling for a re-evaluation of stock definitions. MSA data can be implemented in stock assessment and in a variety of applications, including marine ecosystem description, impact assessment of specific fleets, and stock-rebuilding plans