Objective Disassembly Sequence Planning of Used Mobile Phones Based on Improved Hybrid Graph Disassembly Model

To solve the problems of environmental pollution and waste of resources caused by used mobile phones, the study of objective disassembly sequence planning is carried out for used mobile phones. In view of the connection of mobile phone parts with multiple parts and the need to disassemble components, the concepts of containment, exclusion, and components are integrated into the hybrid graph. An improved hybrid graph is proposed and the improved hybrid graph disassembly model suitable for mobile phone disassembly is established. The ant colony algorithm is used to search for the optimal disassembly sequence, with the objective of minimum disassembly time. Finally, the improved hybrid graph disassembly model is applied to obtain the disassembly solution of HUAWEI Honor 6. The experimental results demonstrate that the disassembly sequence generated by the improved hybrid graph disassembly model can describe the actual disassembly process of disassembling components with less disassembly time.

Optimal Modular Remanufactured Product Configuration and Harvesting Planning for End-of-Life Products

Remanufacturing is a representative product recovery strategy that can improve economic profitability and sustainability by restoring discarded or traded-in used products to a like-new condition. Unlike the production process of new products, remanufacturing requires unique production processes, such as collecting used products and dis(re)assembly. Therefore, several factors need to be considered for the design of remanufactured products. First, when designing a remanufactured product, it is crucial to ensure that the specifications of components meet the customer's requirements because the remanufacturing uses relatively outdated components or modules. In addition, it is necessary to consider the disassembly level and order to facilitate the disassembly process to obtain the desired parts. This study proposes an integrated model to (i) find configuration design suitable for remanufactured products that can maximize customer utility based on End-of-life products, and (ii) establish a harvest plan that determines the optimal disassembly operations and levels. This proposed model can be used as a decisionmaking tool that helps product designers find the appropriate design of remanufactured products while increasing the efficiency of the remanufacturing process.

Identification of Chemical Bonds and Microstructure of Hydrated Tricalcium Silicate (C3S) by a Coupled Micro-Raman/BSE-EDS Evaluation

Identifying the phase evolution and revealing the chemical bonds of hydrated cements accurately is crucial to regulate the performance of cementitious materials. In this paper, a coupled Raman/BSE-EDS analysis was proposed to determine the chemical bonds of tricalcium silicate hydrates and the interface transition zone (ITZ) between inner C-S-H and anhydrates. The results show that the Raman/BSE-EDS method can accurately identify the chemical bonds of inner C-S-H and inner ITZ regions, which confirms the mixed structure of inner C-S-H and nano calcium hydroxide (CH). The inner ITZ shows a lattice change region with a thickness of 700–1000 nm, which can be attributed to the pre-disassembly process of C3S crystal. The successful application of coupled Raman/BSE-EDS provides new insight into the hydration process and multi-structure features of traditional cementitious materials.

All-or-none amyloid disassembly via chaperone-triggered fibril unzipping favors clearance of α-synuclein toxic species

α-synuclein aggregation is present in Parkinson’s disease and other neuropathologies. Among the assemblies that populate the amyloid formation process, oligomers and short fibrils are the most cytotoxic. The human Hsc70-based disaggregase system can resolve α-synuclein fibrils, but its ability to target other toxic assemblies has not been studied. Here, we show that this chaperone system preferentially disaggregates toxic oligomers and short fibrils, while its activity against large, less toxic amyloids is severely impaired. Biochemical and kinetic characterization of the disassembly process reveals that this behavior is the result of an all-or-none abrupt solubilization of individual aggregates. High-speed atomic force microscopy explicitly shows that disassembly starts with the destabilization of the tips and rapidly progresses to completion through protofilament unzipping and depolymerization without accumulation of harmful oligomeric intermediates. Our data provide molecular insights into the selective processing of toxic amyloids, which is critical to identify potential therapeutic targets against increasingly prevalent neurodegenerative disorders.

Micellar Assembly and Disassembly of Organoselenium Block Copolymers through Alkylation and Dealkylation Processes

The aim of this work is to demonstrate that the alkylation and dealkylation of selenium atoms is an effective tool in controlling polymer amphiphilicity and, hence, its assembly and disassembly process in water. To establish this concept, poly(ethylene glycol)-block-poly(glycidyl methacrylate) was prepared. A post-synthesis modification with phenyl selenolate through a base-catalyzed selenium-epoxy ‘click’ reaction then gave rise to the side-chain selenium-containing block copolymer with an amphiphilic character. This polymer assembled into micellar structures in water. However, silver tetrafluoroborate-promoted alkylation of the selenium atoms resulted in the formation of hydrophilic selenonium tetrafluoroborate salts. This enhancement in the chemical polarity of the second polymer block removed the amphiphilic character from the polymer chain and led to the disassembly of the micellar structures. This process could be reversed by restoring the original amphiphilic polymer character through the dealkylation of the cations.

Knowledge Recommendation System for Human-Robot Collaborative Disassembly Using Knowledge Graph

In recent years, more and more attention has been paid to Human-Robot Collaborative Disassembly (HRCD) in the field of industrial remanufacturing. Compared with the traditional manufacturing, HRCD helps to improve the manufacturing flexibility with considering the manufacturing efficiency. In HRCD, knowledge could be obtained from the disassembly process and then provides useful information for the operator and robots to execute their disassembly tasks. Afterwards, a crucial point is to establish a knowledge-based system to facilitate the interaction between human operators and industrial robots. In this context, a knowledge recommendation system based on knowledge graph is proposed to effectively support Human-Robot Collaboration (HRC) in disassembly. A disassembly knowledge graph is constructed to organize and manage the knowledge in the process of HRCD. After that, based on this, a knowledge recommendation procedure is proposed to recommend disassembly knowledge for the operator. Finally, the case study demonstrates that the developed system can effectively acquire, manage and visualize the related knowledge of HRCD, and then assist the human operator to complete the disassembly task by knowledge recommendation, thus improving the efficiency of collaborative disassembly. This system could be used in the human-robot collaboration disassembly process for the operators to provide convenient knowledge recommendation service.

Two-Dimensional Image Based Product Connector Recognition for Robotic Disassembly in Remanufacturing

Remanufacturing has received increasing attention for environmental protection and resource conservation considerations. Disassembly is a crucial step in remanufacturing, is always done manually which is inefficient while robotic disassembly can improve the efficiency of the disassembly. Aiming at the problem of product connector recognition during the robotic disassembly process, we analyze the template matching and feature matching principles based on two-dimensional images. To reduce the computational complexity of traditional template matching, a stepwise search strategy combining coarse and fine is proposed. Based on this a product connector recognition algorithm based on fast template matching and a product connector recognition algorithm based on feature matching is designed. Taking bolts and hexagon nuts as examples, the recognition effects of the two algorithms are compared and analyzed.

An Ontology-Based Method for Semi-Automatic Disassembly of LCD Monitors and Unexpected Product Types

Disassembly is a vital step in any treatment stream of waste electrical and electronic equipment (WEEE), preventing hazardous and toxic chemicals and materials from damaging the ecosystem. However, the large variations and uncertainties in WEEE is a major limitation to the implementation of automation and robotics in this field. Therefore, the advancement of robotic and automation intelligence to be flexible in handling a variety of situations in WEEE disassembly is sought after. This paper presents an ontology-based cognitive method for generating actions for the disassembly of WEEE, with a focus on LCD monitors, handling uncertainties throughout the disassembly process. The system utilizes reasoning about relationships between a typical LCD monitor product, component features, common fastener types, and actions that the system is capable of, to determine 4 key stages of robotic disassembly: component identification, fastener identification, disassembly action generation, and identification of disassembly extent. Further uncertainties in the form of possible failure of action execution is reasoned about to provide new actions, and any unusual scenarios that result in incorrect reasoning outputs are rectified with user-demonstration as a last resort. The proposed method is trialed for the disassembly of LCD monitors and a product unknown to the system, in the form of a DVD-ROM drive.