Study On The Energy Efficiency Improvement Of Engine Remanufacturing System And Its Macro Environmental Benefits

Manufacturing industry involves in enormous aspects and consumes substantial energy.Vigorously boosting the energy efficiency in manufacturing industry has been a primary topic in greent developmentplan for industry(201 6?2020)promulgated by Ministry of Industry and Information Technology.As an environmentally favorable and resource-saving strategic manufacturing paradigm,remanufacturing highly conforms to the ideology of circular economy,and receives intensive attentions from the academic community,industry,and governmental organizations.Currently,the development of remanufacturing industry in China has witnessed a significant increase in recent years.Highly efficient operation is the new requirement and challenge for remanufacturing system under the circular economy strategy.Thus,the investigation on energy efficiency improvement and its environmental benefits would provide fundamental theory and methods to guide highly efficient remanufacturing practice,which have important scientific value and pragmatic significance.Returned cores are regarded as work-blanks in remanufacturing system,which causes numerous uncertain factors.The energy consumption with high dynamic uncertainty,nonlinear variation,and complex constraints complicates the energy efficiency improvement in remanufacturing system.In order to practically solve the problem above and enhance the energy efficiency,this study centered with uncertainties in engine remanufacturing,energy efficiency improvement approaches,and macro environmental benefits,incorporated the theoretical analysis,modeling and simulation,optimization algorithm design,and onsite survey to develop the research task.Firstly,this study introduced the types and connotations of uncertainties,and investigated the mathematical description and propagation analysis method.Then,we established energy optimization models on multi-layer and investigated relevant algorithms and prediction approaches with high precision,robustness,and adaptation.Finally,the assessment model of environmental benefits was established to supports the evaluation of efficiency promotion technologies,and contributes to the policymaking of energy conservation&emission reduction(ECER).This study involved in multiple disciplines with strong comprehensiveness.Details of this paper include the following aspects:(1)The mathematic description and analysis of uncertainties in remanufacturing system was studied.Firstly,connotations,types,and programming methods of uncertainties in the engine remanufacturing system were described.Then,stochastic,fuzzy,and grey parameters were introduced into classic Graphical Evaluation and Review Technique(GERT)network to establish a GERT model with multiple uncertainties.The analytic solution to this model was illustrated based on Mason topology equation,equivalent transfer function,and the properties of moment generating function.Finally,this model was applied to the description of connecting rod remanufacturing process to determine the boundary of branch possibility of processing routes,processing time,and energy consumption.Based on the accuracy of network model validated by Arena simulation,this study investigated the impacts of systematic perturbation and propagation effect on processing time and energy brought by rapid inspection technology and efficient restoration technology.This model enables fast and accurate estimation of values of remanufacturing production indicators.(2)A two-stage energy efficiency optimization method was proposed for remanufacturing equipment,integrating equipment selection and parameter optimization.At the first stage,in terms of the variations of remanufacturing machines,we comprehensively considered the economical,technical,and energy-related indicators,and their values were determined by the life cycle cost,fuzzy synthesis judgment,and energy footprint method,respectively.Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)-based fuzzy decision-making approach was adopted to select the preferential remanufacturing machine.At the second stage,this study developed an improved gene expression programming algorithm to build the prediction models of efficiency(energy efficiency and material efficiency)and made a comparison with conventional response surface methodology based on the data obtained by physical monitoring experiments.The typical multiple objectives optimization method,i.e.,Non-dominated Sorting Genetic Algorithm-?(NSGA-?)algorithm was utilized to compute the optimal combination of processing parameters under the constraint.Finally,an illustrative example of crankshaft remanufacturing practice and laser cladding experiment to verify the effectiveness of two-stage optimization method and also the high accuracy and robustness of empirical energy efficiency model.The parameter optimization of laser cladding equipment showed that,under the constraint of powder efficiency,energy efficiency of optimal parameters would be over 50%higher than that of empirical parameters.(3)Energy efficient scheduling model for remanufacturing processing chain and the corresponding heuristic and meta-heuristic algorithms were developed.Firstly,according to the properties of machine organization,machine interactions,and state-related energy consumption in engine remanufacturing system,this study described the operational rules of fuzzy numbers and systematic constraints.Considering the batch machines,parallel machines,and uncertainty of processing time and routes comprehensively,we developed an energy-saving oriented scheduling model at process-chain level with the strategy of reducing the idle energy of machines.Then,as a meta-heuristic method,we also developed a hormone regulation mechanism based adaptive genetic algorithm and designed relevant operators to solve this scheduling model.Subsequently,as a heuristic method,this study built a scheduling-oriented transition-timed Petri net model solved by A*algorithm in which three heuristic functions were designed according to the optimization objective.To avoid the state space explosion,this work proposed a dynamic window search with new rules.Finally,a cylinder block remanufacturing practice was utilized as an illustrative example.The improved adaptive genetic algorithm and A*algorithm integrated with new dynamic window search could improve the energy efficiency by 9.7%and 7.6%,respectively.In this case,the computational efficiency of the latter was two orders of magnitude higher than the former.(4)This study proposed a Computational General Equilibrium(CGE)model towards the energy efficiency improvement in engine remanufacturing system to quantify its environmental benefits.This model includes five basic blocks:production block,trade block,income&expenditure block,market equilibrium block,and environment block.The algebraic equation set in each block is developed based on the economic theories and rules such as maximum utility,minimum cost,and market closure etc.The data set including Social Accounting Matrix(SAM),share parameters,elasticities of substitution,emission parameters were collected from calibration,onsite survey,and prior references.Programming and simulations on the General Algebraic Modeling System(GAMS)platform revealed the output variation of each sector and the net emission reduction under energy efficiency improvement in engine remanufacturing system.Robustness of the CGE model was validated by the sensitivity analysis.