高职模具类人才培养新模式的研究与实践

为了解决传统教学无法全面培养人才的问题,采用"课程融合+时空耦合+过程结合"的方式开展人才培养研究。以注射模设计与制造生产过程为导向,构建大项目牵引下的跨越课程、跨越学期的课程融合新模式,利用信息通信技术及互联网平台,将互联网与传统教学进行深度融合,创造新的教学生态,构建多元多维互动的时空耦合教学新关系,以全方位评价为引导,构建课程多元多维的评价新机制。以3个班级为对象开展不同模式下的教学,对试验班级成绩进行分析,研究结果表明:课程融合+时空耦合+过程结合新模式培养的学生更好地完成了综合项目,获得了较好的教学效果。     

Improvement of mechanical property and corrosion resistance of Mg-Zn-Nd alloy by bi-direction drawing

Mg-Zn-Nd alloy is a promising biodegradable metal material for surgical staples during the reconstruc-tion of digestive tract due to its good biocompatibility and suitable mechanical properties.However,its deformation property and corrosion resistance should be improved to make better safety and effective-ness of staples.In the present study,bi-direction drawing was adopted to maintain the initial texture characteristics,and improve mechanical property and corrosion resistance of Mg-2Zn-0.5Nd alloy.The results showed that the microstructure after bi-direction did not change too much,but the texture could maintain its initial characteristics.The ductility of the alloy with 60 ％ accumulative area reduction after bi-direction drawing was increased by 70 ％,indicating that an outstanding deformation property of Mg-Zn-Nd alloy can be obtained by bi-direction drawing.The corrosion resistance was also improved after bi-direction drawing compared with that under single direction drawing.     

镍基高温合金锥筒形件拉深旋压成形机理研究

针对镍基高温合金因加工硬化严重成形时极易产生破裂和起皱等典型缺陷的问题,以锥筒形壳体类零件为对象,提出了一种由锥形预制坯经过真空固溶处理后拉深旋压成形锥筒形件的方法,并对其成形机理进行了研究。基于Abaqus/Explicit平台,建立了锥筒形件拉深旋压有限元模型,分析了成形过程中的瞬态等效应力、等效塑性应变、切向应力、壁厚及三向应变分布规律。结果表明:在旋压成形过程中,最大瞬态等效应力位于旋轮接触区及附近区域、最大瞬态等效塑性应变位于坯料口部;瞬态切向压应力最大值位于旋轮接触区,而瞬态切向拉应力最大值位于旋轮接触区附近的两侧区域。筒形段中部壁厚减薄,而坯料口部壁厚增厚。旋压成形试验表明,锥形预制坯经拉深旋压后可获得壁厚均匀的锥筒形件。     

A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility

The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but not worker flexibility. Given the influence and potential of human factors in improving production efficiency and decreasing the cost in practical production systems, we propose a mathematical model of an extended FJSP with worker flexibility (FJSPW). A hybrid artificial bee colony algorithm (HABCA) is presented to solve the proposed FJSPW. For the HABCA, effective encoding, decoding, crossover and mutation operators are designed, and a new effective local search method is developed to improve the speed and exploitation ability of the algorithm. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the HABCA. Extensive computational experiments carried out to compare the HABCA with some well-performing algorithms from the literature confirm that the proposed HABCA is more effective than these algorithms, especially on large-scale FJSPW instances.     

Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain

Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.     

An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production

Energy-efficient scheduling is highly necessary for energy-intensive industries, such as glass, mould or chemical production. Inspired by a real-world glass-ceramics production process, this paper investigates a bi-criteria energy-efficient two-stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time-of-use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented ε-constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem-tailored constructive heuristic method with local search strategy, a bi-objective tabu search algorithm and a bi-objective ant colony optimisation algorithm are developed to deal with medium- and large-scale problems. Extensive computational experiments are conducted, and a real-world case is solved. The results show effectiveness of the proposed methods, in particular the bi-objective tabu search.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

Automatic design for shop scheduling strategies based on hyper-heuristics: A systematic review

Against the background of smart manufacturing and Industry 4.0, how to achieve real-time scheduling has become a problem to be solved. In this regard, automatic design for shop scheduling based on hyper-heuristics has been widely studied, and a number of reviews and scheduling algorithms have been presented. Few studies, however, have specifically discussed the technical points involved in algorithm development. This study, therefore, constructs a general framework for automatic design for shop scheduling strategies based on hyper-heuristics, and various state-of-the-art technical points in the development process are summarized. First, we summarize the existing types of shop scheduling strategies and classify them using a new classification method. Second, we summarize an automatic design algorithm for shop scheduling. Then, we investigate surrogate-assisted methods that are popular in the current algorithm field. Finally, current problems and challenges are discussed, and potential directions for future research are proposed.     

纺粘非织造聚合物拉伸模型初探

为探究纺粘非织造工艺中工艺参数对纤维最终直径的影响,文章基于纺粘非织造聚合物拉伸过程,构建了纺粘非织造聚合物拉伸理论模型,并应用MATLAB对模型进行数值计算。同时,选取纺粘工艺参数中的气流初始速度、聚合物初始温度、聚合物质量流量3个因素,通过控制变量法比较观察不同方案下经过数值求解后得到的纤维直径,得出3个因素分别对纤维最终直径的影响。结果表明,气流初始速度越大,聚合物初始温度越高,聚合物质量流量越小,最终形成的纤维直径越细。