Application and planning of an energy-oriented stochastic disassembly line balancing problem.

End-of-life (EOL) products are getting more and more attention as a result of the rapid decline in environmental resources and the dramatic rise in population at the moment. Disassembly is a crucial step in the reuse of EOL products. However, the disassembly process for EOL products is highly uncertain, and the disassembly planning method may not produce the anticipated outcomes in actual implementation. Based on the physical nature of the product disassembly process with multiple uncertain variables, certainty disassembly cannot adequately characterize the uncertain variables effectively. Uncertainty disassembly takes into account the changes in parts caused by product use, such as wear and corrosion, which can better coordinate the arrangement of disassembly tasks and better match the actual remanufacturing process. After analysis, it was found that most of studies on uncertain disassembly focus on the economic efficiency perspective and lack of energy consumption considerations. For the gaps in the current study, this paper proposes a stochastic energy consumption disassembly line balance problem (SEDLBP) and constructs a mathematical model of SEDLBP based on the disassembly of spatial interference matrix, In this model, the energy consumption generated by the disassembly operation and workstation standby is not a constant value but is generated stochastically in a uniformly distributed interval. In addition, an improved social engineering optimization algorithm that incorporates stochastic simulation (SSEO) is proposed in this paper to effectively address the issue. The incorporation of swap operators and swap sequences in SSEO makes it possible to solve discrete optimization problems efficiently. A comparison of a case study with some well-tested intelligent algorithms demonstrates the efficacy of the solutions produced by the proposed SSEO.

Environment-oriented disassembly planning for end-of-life vehicle batteries based on an improved northern goshawk optimisation algorithm.

Due to environmental pollution and resource shortages, the electric vehicle industry has been developing swiftly, and the market demand for batteries, as an essential part of electric vehicles, has also surged. Proper disassembly of end-of-life vehicle batteries (ELV batteries) is necessary to achieve the integrity and closure of their life cycle, promote the development of green remanufacturing, effectively reduce the pollution of the environment caused by metal ion leakage, and reduce people's dependence on natural resources to a certain extent. To schedule the disassembly operations of ELV batteries more rationally and further promote their disassembly quality and efficiency, this paper proposes a dual-objective disassembly sequence planning (DSP) optimisation model, which aims to minimise the hazard index and energy cost during ELV battery disassembly operations. Since the proposed model is a complex NP-hard optimisation problem, this study develops an efficient metaheuristic algorithm for solving this model based on the northern goshawk optimisation algorithm. The main algorithm adds two types of discrete recombination operators and a local search operator. At the same time, the predatory behaviour of the goshawk is optimised by combining the characteristics of the disassembly sequence planning problem to improve its performance. Finally, the disassembly of the battery of a Tesla Model 1 is used as a case study to demonstrate the effectiveness and feasibility of the proposed method.

Distinguishing heroin abuse from codeine administration in the urine of Chinese people by UPLC-MS-MS.

Heroin is a highly addictive drug, and heroin abuse is considered to be a serious criminal act. The major metabolite of heroin, morphine, can usually be detected as evidence of heroin abuse. However, it is difficult to determine heroin use when morphine and codeine are both detected, because codeine use will also result in the presence of morphine in urine. Therefore, it is important to distinguish heroin abuse from codeine administration. In this study, urine samples from 21 volunteers with various ingestion patterns of a compound codeine phosphate oral solution were used as negative controls, and urine samples from 89 alleged heroin users were used as positive controls. Urine from single and multiple doses of codeine administration were collected at different time points for a systematic comparison. After protein precipitation, the urine samples were analyzed for the presence of free morphine, free codeine and their metabolites by ultra-performance liquid chromatography-tandem mass spectrometry. The method of percentiles, with median and standard interquartile ranges, was used to describe and analyze the data based on the normality of the distribution. The ratios of concentration of morphine and morphine to codeine were found to be the possible criteria to distinguish heroin users from codeine users in Chinese people.

[Comparison of morphine and codeine concentration in urines of heroin abusers and codeine users].

OBJECTIVE: To compare morphine and codeine concentration in urines of heroin abusers and codeine users and to discuss the judgment index to distinguish between heroin abuser and codeine user. METHODS: The urines of heroin abusers and codeine users were collected at different time periods. After protein precipitation, the urine samples were conducted for the qualitative and quantitative analysis of morphine and codeine by UPLC-MS/MS. And the results were all statistically analyzed. RESULTS: Statistical analysis showed that morphine and codeine concentration in urines of heroin abusers and codeine users were both abnormal distributions. The probability of the heroin abuser would be more than 95% and less than 5% for the codeine user when the concentration of morphine in urine sample was more than 67 ng/mL. The probability of the codeine user would be more than 95% and less than 5% for the heroin abuser when the concentration of morphine in urine sample was less than 67 ng/mL. CONCLUSION: The morphine concentration in urine could be used as a criterion to distinguish the heroin abuser from the codeine user, while the codeine concentration could not.

[Simultaneous determination of opioid compounds in human urine by UPLC-MS/MS].

OBJECTIVE: To propose a method for simultaneous determination of codeine(COD), 6-monoacetyl-morphine (6-MAM), morphine (MOR), morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G) in human urine by ultra performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS). METHODS: After precipitation of protein by acetonitrile, the urine samples, with added the morphine-d3 (MOR-d3) and morphine-3-Glucuronide-d3 (M3G-d3) as internal standards, were pre-treated by Sirocco protein precipitation plate, and then analyzed by UPLC-MS/MS. RESULTS: The limit of detection was 0.2 ng/mL for both COD and MAM, the limit of quantitation was 0.5 ng/mL for both COD and MAM. The limit of detection was 0.5 ng/mL for MOR, M3G and M6G, the limit of quantitation was 1 ng/mL for them. The linear correlation coefficients were not less than 0.9997, both the inter-day and intra-day precisions were less than 10%, the recoveries were in the range of 70.0% to 98.3%, the matrix effects were about 50.5% to 99.0%. CONCLUSION: This proposed method is simple, rapid and accurate, it could be applied in forensic toxicological analysis.