Cooperative Disassembly Research Articles

Research on the Human–Robot Collaborative Disassembly Line Balancing of Spent Lithium Batteries with a Human Factor Load

The disassembly of spent lithium batteries is a prerequisite for efficient product recycling, the first link in remanufacturing, and its operational form has gradually changed from traditional manual disassembly to robot-assisted human–robot cooperative disassembly. Robots exhibit robust load-bearing capacity and perform stable repetitive tasks, while humans possess subjective experiences and tacit knowledge. It makes the disassembly activity more adaptable and ergonomic. However, existing human–robot collaborative disassembly studies have neglected to account for time-varying human conditions, such as safety, cognitive behavior, workload, and human pose shifts. Firstly, in order to overcome the limitations of existing research, we propose a model for balancing human–robot collaborative disassembly lines that take into consideration the load factor related to human involvement. This entails the development of a multi-objective mathematical model aimed at minimizing both the cycle time of the disassembly line and its associated costs while also aiming to reduce the integrated smoothing exponent. Secondly, we propose a modified multi-objective fruit fly optimization algorithm. The proposed algorithm combines chaos theory and the global cooperation mechanism to improve the performance of the algorithm. We add Gaussian mutation and crowding distance to efficiently solve the discrete optimization problem. Finally, we demonstrate the effectiveness and sensitivity of the improved multi-objective fruit fly optimization algorithm by solving and analyzing an example of Mercedes battery pack disassembly.

An improved artificial bee colony algorithm for the multi-objective cooperative disassembly sequence optimization problem considering carbon emissions and profit

The disassembly and recycling of electronic waste are essential for realizing residual value, lowering carbon emissions and fostering sustainable development. This article addresses multi-objective cooperative disassembly planning and algorithm optimization for waste mobile phones. The model aims to reduce carbon emissions during the disassembly process and to increase profits. Moreover, an improved artificial bee colony (IABC) algorithm is introduced to address the model. The model is validated using Apple smartphones as a case study. The results indicate that cooperative disassembly can lower carbon emissions by 21.04% and increase profits by 40.04% more than sequential disassembly. The efficiency of the improved algorithm was assessed using Friedman and Nemenyi tests. Significant differences were found between the IABC and the other three algorithms, with significant P-values of P = 0.001, P = 0.006 and P = 0.024. It is demonstrated that the proposed model and improved algorithm exhibit reliability and superiority.

Robotic ease of Disassembly Metric (Re-DiM) for human robot cooperative disassembly: A case study for a vacuum cleaner

Remanufacturing, a beacon of economic and ecological alignment, hinges on disassembly’s complexity. As both manual and robotic approaches face challenges, systems in which human and robots can work iteratively offer adaptable solutions, curbing the required system flexibility at acceptable capital expenditure. However, today no metrics exist to evaluate the ease of disassembly of product designs when considering a combination of manual and robotic disassembly Therefore, this study extends the existing ease of Disassembly Metric (e-DiM) for designers, policymakers, and recyclers in anticipation of the industrialization of human-robot cooperative disassembly systems. For the development of such a metric the expected limitations of robotic disassembly systems are first discussed based on prior research. Subsequently, a set of criteria are presented to define which operations can be performed successfully in a flexible system. Finally, the Robotic ease of Disassembly metric (Re-DiM) is introduced, which serves to comprehensively evaluate both manual and robotic disassembly times. To validate Re-DiM’s applicability, the ease of both manual and robotic disassembly is evaluated for all critical components of a robotic vacuum cleaner. The presented case study highlights today’s robotic disassembly challenges, underscoring also the relevance of novel design for robotic disassembly approaches.

Long-Range Cooperative Disassembly and Aging During Adenovirus Uncoating

The disassembly of a virus' protein shell must happen at the right time to ensure transfer of the viral genome to its host. New experiments reveal that aging determines the dynamics of this unraveling.

HIV-1 uncoating by release of viral cDNA from capsid-like structures in the nucleus of infected cells.

HIV-1 replication commences inside the cone-shaped viral capsid, but timing, localization, and mechanism of uncoating are under debate. We adapted a strategy to visualize individual reverse-transcribed HIV-1 cDNA molecules and their association with viral and cellular proteins using fluorescence and correlative-light-and-electron-microscopy (CLEM). We specifically detected HIV-1 cDNA inside nuclei, but not in the cytoplasm. Nuclear cDNA initially co-localized with a fluorescent integrase fusion (IN-FP) and the viral CA (capsid) protein, but cDNA-punctae separated from IN-FP/CA over time. This phenotype was conserved in primary HIV-1 target cells, with nuclear HIV-1 complexes exhibiting strong CA-signals in all cell types. CLEM revealed cone-shaped HIV-1 capsid-like structures and apparently broken capsid-remnants at the position of IN-FP signals and elongated chromatin-like structures in the position of viral cDNA punctae lacking IN-FP. Our data argue for nuclear uncoating by physical disruption rather than cooperative disassembly of the CA-lattice, followed by physical separation from the pre-integration complex.

3D-based multi-objective cooperative disassembly sequence planning method for remanufacturing

Large-scale and high-efficiency disassembly is an important means to improve the efficiency and benefits of remanufacturing of waste products. This paper proposes a 3D-based multi-objective collaborative disassembly sequence planning method for remanufacturing products, which can effectively improve efficiency of the disassembly line. Firstly, combining entropy weight method and PROMETHEE II method, the priority disassembly level of the waste product parts is established. According to the disassembly level ranking of the parts, one or more target disassembly parts with higher priority are selected. Secondly, rapid-growing random tree algorithm is used to layer the three-dimensional product assembly structure, and the disassembly sequence of the single-objective part is calculated by the constraint relationship of different layer parts. Finally, the co-evolution algorithm is used to coordinate multiple single-objective part disassembly sequences to obtain the overall optimal multi-objective part disassembly sequence, which is the sequence plan with the minimum required number of disassembly parts. Through the disassembly case analysis of two-stage reducer, the correctness and effectiveness of the planning method for coordinated disassembly of multi-objective parts are verified.

Product cooperative disassembly sequence and task planning based on genetic algorithm

To improve the disassembly efficiency, cooperative disassembly is essential for complex products. Operator task allocation is a significant challenge for cooperative disassembly sequence planning; however, it has not been studied previously to the best of our knowledge. To deal with this problem, a novel cooperative disassembly sequence and task planning (CDS&TP) method was proposed based on the genetic algorithm. A mathematical model of the CDS&TP problem was constructed based on the product’s disassembly hybrid graph model (DHGM). Focusing on the characteristics of the CDS&TP, a multi-layer chromosome coding method was proposed to describe the node layer and operator constraint layer. Thus, the initial population could be deduced through the node layer and operator constraints relationship rule model, which was proposed to construct the operator constraint and node layers. To obtain the task sequence of each operator and the disassembly time of each sequence, a chromosome fitness calculation formula was presented based on the disassembly set, which is the collection of all of the detachable nodes with a disassembly priority higher than the node. The chromosome evolution rules, such as the selection, crossover, and mutation operators, were redesigned to obtain the (approximate) optimal multiplayer cooperative disassembly sequences and task planning. Finally, a case study was proposed to validate the method.

Selective cooperative disassembly planning based on multi-objective discrete artificial bee colony algorithm

Disassembly sequencing has significant effects on the performance of remanufacturing and recycling of used or discarded products. Studies on disassembly sequence optimization have largely focused on sequential disassembly. However, for large or complex products sequential disassembly takes long time to complete and is rather inefficient since it removes only one part or subassembly at a time with only one operator assigned to disassemble a product. This work studies selective cooperative disassembly sequence planning (SCDSP) problem which is essential to disassemble large or complex products in an efficient way. Similar to sequential disassembly planning, SCDSP aims at finding the optimal disassembly task sequence, but is more complicated. SCDSP is a nonlinear NP-complete combinatorial optimization problem, and evolutionary algorithms can be adopted to solve it. In this paper exclusive and cooperative relationships are introduced as additional constraints besides the common precedence relationship. A novel procedure to generate feasible cooperative disassembly sequences (GFCDS) is proposed. A mathematical programming model of SCDSP is developed based on the parallel disassembly characteristics with two optimization objectives i.e. disassembly time and profit, considered. A multi-objective evolutionary algorithm (MOEA), i.e., multi-objective discrete artificial bee colony optimization (MODABC), is adopted to solve the problem to create the Pareto frontier. This approach is applied to real-world disassembly processes of two products (a small product and a medium/large one) to verify its feasibility and effectiveness. Also, the proposed method is compared with the well-known NSGA-II. For our comparative study, the nondominated solutions of the two MOEAs are compared in both cases, and two quantitative metrics, i.e., inverted generational distance (IGD) and spacing (SP), are adopted to further measure the algorithm performance. Results indicate that the set of nondominated solutions from MODABC are better for each instance tested, and the Pareto front is overall superior to that from NSGA-II. For both cases, IGD and SP are decreased by up to 81.5% and 62.2%, respectively.

Regulated proteolysis of a transcription factor complex is critical to cell cycle progression in Caulobacter crescentus

Cell cycle transitions are often triggered by the proteolysis of key regulatory proteins. In Caulobacter crescentus, the G1-S transition involves the degradation of an essential DNA-binding response regulator, CtrA, by the ClpXP protease. Here, we show that another critical cell cycle regulator, SciP, is also degraded during the G1-S transition, but by the Lon protease. SciP is a small protein that binds directly to CtrA and prevents it from activating target genes during G1. We demonstrate that SciP must be degraded during the G1-S transition so that cells can properly activate CtrA-dependent genes following DNA replication initiation and the reaccumulation of CtrA. These results indicate that like CtrA, SciP levels are tightly regulated during the Caulobacter cell cycle. In addition, we show that formation of a complex between CtrA and SciP at target promoters protects both proteins from their respective proteases. Degradation of either protein thus helps trigger the destruction of the other, facilitating a cooperative disassembly of the complex. Collectively, our results indicate that ClpXP and Lon each degrade an important cell cycle regulator, helping to trigger the onset of S phase and prepare cells for the subsequent programmes of gene expression critical to polar morphogenesis and cell division.

Product cooperative disassembly sequence planning based on branch-and-bound algorithm

This paper focuses on the cooperative disassembly sequence planning (CDSP) problem which is essential to disassembly a large and complex product in practice. A disassembly hybrid graph model (DHGM) is constructed to describe the mating contact and noncontact priority relationships among constituting product components. Thus, the disassemblability constraint expression can be deduced from it by reasoning. The CDSP is different from the disassembly sequence planning except for they are NP-complete. Therefore, a novel method is presented to generate cooperative disassembly hierarchical tree (CDHT) from the DHGM based on branch-and-bound algorithm in which two user-defined variables are introduced to control the size of the CDHT .The optimal solutions with a minimal disassembly time are derived according to the objection function. Finally, an example illustrates the proposed method.

Automatic cooperative disassembly robotic system: Task planner to distribute tasks among robots

This paper presents a task planner based on decision trees. Two different types of cooperative tasks are described: common task and parallel task. In the first type of task two or more robots are required to accomplish the task. In the second type, several tasks can be performed in parallel by different robots to reduce the total disassembly time. The planner presented is based on a hierarchical representation of the product and performs the distribution of the tasks among robots using decision trees. The system takes into consideration the work area of each robot and its own characteristics. The work cell can be composed of j robotic manipulators. Finally, a practical application of a PC disassembly system is shown.

Two divergent endo-beta-1,4-glucanase genes exhibit overlapping expression in ripening fruit and abscising flowers.

Two structurally divergent endo-beta-1,4-glucanase (EGase) cDNAs were cloned from tomato. Although both cDNAs (Cel1 and Cel2) encode potentially glycosylated, basic proteins of 51 to 53 kD and possess multiple amino acid domains conserved in both plant and microbial EGases, Cel1 and Cel2 exhibit only 50% amino acid identity at the overall sequence level. Amino acid sequence comparisons to other plant EGases indicate that tomato Cel1 is most similar to bean abscission zone EGase (68%), whereas Cel2 exhibits greatest sequence identity to avocado fruit EGase (57%). Sequence comparisons suggest the presence of at least two structurally divergent EGase families in plants. Unlike ripening avocado fruit and bean abscission zones in which a single EGase mRNA predominates, EGase expression in tomato reflects the overlapping accumulation of both Cel1 and Cel2 transcripts in ripening fruit and in plant organs undergoing cell separation. Cel1 mRNA contributes significantly to total EGase mRNA accumulation within plant organs undergoing cell separation (abscission zones and mature anthers), whereas Cel2 mRNA is most abundant in ripening fruit. The overlapping expression of divergent EGase genes within a single species may suggest that multiple activities are required for the cooperative disassembly of cell wall components during fruit ripening, floral abscission, and anther dehiscence.