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

Towards Reuse and Recycling of Lithium-ion Batteries: Tele-robotics for Disassembly of Electric Vehicle Batteries

Disassembly of electric vehicle batteries is a critical stage in recovery, recycling and re-use of high-value battery materials, but is complicated by limited standardisation, design complexity, compounded by uncertainty and safety issues from varying end-of-life condition. Telerobotics presents an avenue for semi-autonomous robotic disassembly that addresses these challenges. However, it is suggested that quality and realism of the user's haptic interactions with the environment is important for precise, contact-rich and safety-critical tasks. To investigate this proposition, we demonstrate the disassembly of a Nissan Leaf 2011 module stack as a basis for a comparative study between a traditional asymmetric haptic-'cobot' master-slave framework and identical master and slave cobots based on task completion time and success rate metrics. We demonstrate across a range of disassembly tasks a time reduction of 22%-57% is achieved using identical cobots, yet this improvement arises chiefly from an expanded workspace and 1:1 positional mapping, and suffers a 10-30% reduction in first attempt success rate. For unbolting and grasping, the realism of force feedback was comparatively less important than directional information encoded in the interaction, however, 1:1 force mapping strengthened environmental tactile cues for vacuum pick-and-place and contact cutting tasks.Comment: 21 pages, 12 figures, Submitted to Frontiers in Robotics and AI; Human-Robot Interactio

An integrated approach for remanufacturing job shop scheduling with routing alternatives.

Remanufacturing is a practice of growing importance due to increasing environmental awareness and regulations. However, the stochastic natures inherent in the remanufacturing processes complicate its scheduling. This paper undertakes the challenge and presents a remanufacturing job shop scheduling approach by integrating alternative routing assignment and machine resource dispatching. A colored timed Petri net is introduced to model the dynamics of remanufacturing process, such as various process routings, uncertain operation times for cores, and machine resource conflicts. With the color attributes in Petri nets, two types of decision points, recovery routing selection and resource dispatching, are introduced and linked with places in CTPN model. With time attributes in Petri nets, the temporal aspect of recovery operations for cores as well as the evolution dynamics in cores\u27 operational stages is mathematically analyzed. A hybrid meta-heuristic algorithm embedded scheduling strategy over CTPN is proposed to search for the optimal recovery routings for worn cores and their recovery operation sequences on workstations, in minimizing the total production cost. The approach is demonstrated through the remanufacturing of used machine tool and its effectiveness is compared against another two cases: baseline case with fixed recovery process routings and case 2 using standard SA/MST

Disassembly Planning and Costing Through Petri Net Approach

In the current consumer oriented environment, many new products appear in the market almost on a daily basis. Lured by advertisements and tempted by new product features, customers are constantly purchasing newer products. Acquiring newer products for often leads to throwing out older ones, but it is a totally different story for manufacturers. They need to consider the best way to reuse a product both for economic purposes and for environmental protection. Considerations for them often include: how to minimize total disassembly cost, how to achieve the lowest total disassembly time at each processing step, and how to sort valuable parts from hazardous parts as early as possible during the disassembly procedure. In this paper, we use a Disassembly Petri-Net (DPN) to generate the Disassembly Process Plan (DPP). This plan is a sequence of disassembly tasks from the initial stage of the whole product to the final stage where each part is separated from the other parts. This disassembly plan is very valuable for product recycling or remanufacturing. Prior to having the DPN, we apply an algorithm to generate a Disassembly Precedence Matrix (DPM) helped by the construction steps involved in SolidWorks™, a solid model software used to create the part in the first place. From the DPN, we find all feasible paths and generate the corresponding costs of disassembly based upon tool changes, changes in direction of the movement and individual part characteristics (e.g. hazardous components and recycle component). Cost data was extracted from previously published studies by Boothroyd et al. to obtain the handling time and disassembly time. Afterwards, we developed the optimal or near-optimal DPP for the best time and cost based disassembly options. In summary, this paper presents a systematic method to disassemble a part into its individual components and provides a cost figure for doing so. This is in contrast with many studies reported in the literature in that they concentrate either on a measure of disassembly complexity, or even if cost is presumably the driving force, their costs are arbitrary costs based on pre-selected values for such things as tool change penalty, disassembly direction change penalty or penalty for delaying removal of hazardous materials. In this paper, we are using disassembly times based on experimental work and/or industrial experience. Given the correct labor rate, our cost evaluation indeed yields a realistic cost value