Coordinated optimisation of platform-driven product line planning by bilevel programming

Product line planning (PLP) aims at an optimal combination of product feature offerings, suggesting itself to be a determinant decision for a company to satisfy diverse customer needs and gain competitive advantages. Fulfilment of planned product lines must make trade-offs between product variety and production costs. To balance the costs of product lines, manufacturers often adopt a product platform configuration (PPC) approach to redesign product and process platforms by adding new modules to the legacy platforms. The PPC is an effective means of providing product variety while controlling the manufacturing costs. The PLP and PPC problems have traditionally been investigated separately in the marketing research and engineering design fields. It is important to coordinate PLP and PPC decisions within a coherent optimisation framework. This paper proposes a bilevel mixed 0–1 nonlinear programming model to formulate coordinated optimisation for platform-driven product line planning. The upper level deals with the PLP problem by maximising the profit of an entire product line, whilst the lower level copes with the multiple product platforms optimisation for the optimal PPC in accordance with the upper level decisions of product line structure. To solve this bilevel programming model, a bilevel genetic algorithm is developed to find the optimal solution. A case study of coordinated optimisation between an automobile line and its product platforms is presented to demonstrate the feasibility and effectiveness of the proposed bilevel programming in comparison with a typical ‘all-in-one’ approach and a non-joint optimisation programming.     

Ant colony optimisation with elitist ant for sequencing problem in a mixed model assembly line

Optimised sequencing in the Mixed Model Assembly Line (MMAL) is a major factor to effectively balance the rate at which raw materials are used for production. In this paper we present an Ant Colony Optimisation with Elitist Ant (ACOEA) algorithm on the basis of the basic Ant Colony Optimisation (ACO) algorithm. An ACOEA algorithm with the taboo search and elitist strategy is proposed to form an optimal sequence of multi-product models which can minimise deviation between the ideal material usage rate and the practical material usage rate. In this paper we compare applications of the ACOEA, ACO, and two other commonly applied algorithms (Genetic Algorithm and Goal Chasing Algorithm) to benchmark, stochastic problems and practical problems, and demonstrate that the use of the ACOEA algorithm minimised the deviation between the ideal material consumption rate and the practical material consumption rate under various critical parameters about multi-product models. We also demonstrate that the convergence rate for the ACOEA algorithm is significantly more than that for all the others considered.     

Ergonomics in assembly line balancing based on energy expenditure: a multi-objective model

In many assembly systems, ergonomics can have great impact on productivity and human safety. Traditional assembly systems optimisation approaches consider only time and cost variables, while few studies include also ergonomics aspects. In this study, a new multi-objective model for solving assembly line balancing problem is developed and discussed in order to include also the ergonomics aspect. First, based on main features of assembly workstations, the energy expenditure concept is used in order to estimate the ergonomics level, thanks to a new technique, called Predetermined Motion Energy System, which helps rapidly estimate the energy expenditure values. Then, a multi-objective approach, based on four different objective functions, is introduced in order to define the efficient frontiers of optimal solutions. To complete the study, a simple numerical example for a real case is presented to analyse the behaviour of Pareto frontiers varying several parameters linked to the energy and time value.     

Product quality improvement method in manufacturing process based on kernel optimisation algorithm

Quality data in manufacture process has the features of mixed type, uneven distribution, dimension curse and data coupling. To apply the massive manufacturing quality data effectively to the quality analysis of the manufacture enterprise, the data pre-processing algorithm based on equivalence relation is employed to select the characteristic of hybrid data and preprocess data. KML-SVM (Optimised kernel-based hybrid manifold learning and support vector machines algorithm) is proposed. KML is adopted to solve the problems of manufacturing process quality data dimension curse. SVM is adopted to classify and predict low-dimensional embedded data, as well as to optimise support vector machine kernel function so that the classification accuracy can be maximised. The actual manufacturing process data of AVIC Shenyang Liming Aero-Engine Group Corporation Ltd is demonstrated to simulate and verify the proposed algorithm.     

Modelling and optimisation of energy-efficient U-shaped robotic assembly line balancing problems

Within U-shaped assembly lines, the increase of labour costs and subsequent utilisation of robots has led to growing energy consumption, which is the current main expense of auto and electronics industries. However, there are limited researches concerning both energy consumption reduction and productivity improvement on U-shaped robotic assembly lines. This paper first develops a nonlinear multi-objective mixed-integer programming model, reformulates it into a linear form by linearising the multiplication of two binary variables, and then refines the weight of multiple objectives so as to achieve a better approximation of true Pareto frontiers. In addition, Pareto artificial bee colony algorithm (PABC) is extended to tackle this new complex problem. This algorithm stores all the non-dominated solutions into a permanent archive set to keep all the good genes, and selects one solution from this set to overcome the strong local minima. Comparative experiments based on a set of newly generated benchmarks verify the superiority of the proposed PABC over four multi-objective algorithms in terms of generation distance, maximum spread, hypervolume ratio and the ratio of non-dominated solution.     

Sustainable disassembly line balancing model based on triple bottom line

End of life (EOL) phase of a product is receiving more attention due to increase in environmental concerns, and many studies have been conducted for value creation in EOL, focusing on concepts as remanufacturing, reuse and recycling in sustainable production manner. This study especially focuses on one of global problem, e-waste. To minimise the amount of wastes and maximise recovered materials from EOL, disassembly is one of the most important concept, associated with reuse, and balancing disassembly line in an optimal way is essential for organisations. In disassembly line balancing (DLB), not only precedence of tasks, but also risk criteria related to environment and human safety should be considered for sustainability. The aim of this study is to propose a model based on triple bottom line (TBL) dimensions, i.e. human safety, environmental safety and business criteria. To achieve sustainability in DLB, and for risk assessment in sustainable DLB, it had been decided to use a multi-criteria method, i.e. TODIM, acronym in Portuguese of ‘Tomada de Decisão Iterativa Multicritério’. The proposed model included 22 disassembly criteria categorised under TBL dimensions, which are derived from the literature. Implementation of the study was conducted for computer disassembly processes, and as a result of the study approximately 12% an improvement in cycle time was succeeded. In the long run, the integration of sustainability in disassembly operations may contribute to the competitive advantage of the company in terms of differentiation and corporate image by achieving business, environment and human targets simultaneously.     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Industrial robot layout based on operation sequence optimisation

The robot layout is one of the primary problems in the robot work cell design. An optimal layout not only makes the robotic end-effector reach the desired position with the desired orientation, but also minimises the robot cycle time for completing a given task with collision avoidance. There may be many feasible robot operation sequences for a given task. The optimisation of operation sequence for a robot placed in a fixed location is NP-complete. There may be different optimal operation sequences as the robot is placed in the different locations. Hence the problem of robot layout is quite complex. This paper presents a method of industrial robot layout based on operation sequence optimisation. The robot motion control model with velocity, acceleration and jerk is established. The feasible space of robot base is calculated and then divided into discrete grids before the optimisations. Then the ant colony algorithm is applied to optimise the operation sequence for each grid. The adjacent grids are merged or divided enough times to form the bigger grids. The pattern search algorithm is adopted to solve the local optimal position and orientation of the robot base in each big grid, and the global optimal layout is found through the comparison of the local solutions. The industrial robot layout method has been applied to the work cell design for car door welding.     

Tool path optimisation for flank milling ruled surface based on the distance function

This paper deals with optimised tool path generation for five-axis flank milling using signed point-to-surface distance function. The main idea is that the geometrical deviations between the design surface and the machined surface are minimised by fine tuning the cutter locations. Based on the tangency conditions in envelope theory, the analytic representation of the envelope surface of a cutter undergoing five-axis motion is first obtained. Then the geometrical deviations between the envelope surface (i.e. machined surface) and the design surface are calculated. Optimisation of the five-axis tool path is modeled as the fine tuning of the initial cutter locations under the minimum zone criterion recommended by ANSI and ISO, which requires minimisation of the maximum geometrical deviation between the design surface and the envelope surface. Using the signed point-to-surface distance function, tool path optimisation for finish milling is formulated as a constrained optimisation problem. Based on the first-order Taylor approximation of the signed distance function, two sequential approximation algorithms for the Minimax and Least Square optimisations are developed. Numerical examples, in which a conical tool is chosen as a special case of flank machining ruled surface, verify the proposed strategy.     

Clamping-sequence optimisation based on heuristic algorithm for sheet-metal components

The traditional clamping-sequence optimisation of sheet-metal parts requires many complicated finite element analyses, and clamping-sequence planning does not account for the springback from clamp-release. Therefore, this paper proposes a new optimisation method based on a heuristic algorithm. We first propose a new contact model of parts, clamps and supporting locators to analyse assembly deformation. Then, we use the distance between the actual and nominal positions to evaluate the clamp layout. Finally, we apply the heuristic algorithm to optimise the clamping sequence. We illustrate the proposed method with a case study of a taillight bracket, whose results show that the method of clamping-sequence optimisation can effectively decrease the deformation of sheet metal from clamping.     

A MCVRP-based model for PCB assembly optimisation on the beam-type placement machine

The beam-type placement machine is capable of picking up multiple components simultaneously from the feeders in printed circuit board (PCB) assembly. Simultaneous pickup occurs only if the heads in the beam are aligned with the feeders and the nozzle-types on these heads match with the component-types on the feeders. In order to minimise the assembly cycle time, the optimisation problem is decomposed into two sub-problems, the pickup combination and sequencing problem, and the placement cluster and sequencing problem. These two sub-problems are simultaneously solved by the proposed hybrid genetic algorithm (HGA). The pickup combination and sequencing problem is similar to the popular multi-compartment vehicle routing problem (MCVRP); a genetic algorithm (GA) for the MCVRP is therefore modified and applied to solving the pickup combination and sequencing problem. A greedy heuristic algorithm is used to solve the placement cluster and sequencing problem. The numerical experiments reveal that the HGA outperforms the algorithms proposed by previous papers.     

基于CAN总线的食品包装生产线控制系统的设计

提出了基于CAN 总线技术的食品包装生产线控制系统的设计,给出了系统整体结构,同时阐述了CAN节点控制器的硬、软件设计方法.结果证明:该系统结构简单、运行可靠、易于调整,提高了生产管理水平和工作效率,为企业生产和管理人员及时了解远程生产现场的状况提供了可能.     

企业产品包装竞争的价值链分析

着重论述了价值链的内涵,价值链与产品包装的竞争优势,企业产品包装设计的基本要求,价值链与产品包装竞争策略,对现代企业产品包装竞争的价值链分析具有重要的决策指导意义.     

A multi-objective distribution-free model and method for stochastic disassembly line balancing problem

End-of-life product recycling is a hot research topic in recent years, which can reduce the waste and protect the environment. To disassemble products, the disassembly line balancing is a principal problem that selects tasks and assigns them to a number of workstations under stochastic task processing times. In existing works, stochastic task processing times are usually estimated by probability distributions or fuzzy numbers. However, in real-life applications, only their partial information is accessible. This paper studies a bi-objective stochastic disassembly line balancing problem to minimise the line design cost and the cycle time, with only the knowledge of the mean, standard deviation and upper bound of stochastic task processing times. For the problem, a bi-objective chance-constrained model is developed, which is further approximated into a bi-objective distribution-free one. Based on the problem analysis, two versions of the ?-constraint method are proposed to solve the transformed model. Finally, a fuzzy-logic technique is adapted to propose a preferable solution for decision makers according to their preferences. A case study is presented to illustrate the validity of the proposed models and algorithms. Experimental results on 277 benchmark-based and randomly generated instances show the efficiency of the proposed methods.     

包装生产线机械设备的自动化

分析包装线上设备的构成,专业化程度,提出包装设备半自动及全自动的需求,尤其指出重袋包装线实用自动化的构想。     

Fixture layout optimisation based on a non-domination sorting social radiation algorithm for auto-body parts

Auto-body compliant parts are easily deformed during clamping and welding, and fixture layout is very important to the final product quality. However, it is very difficult to design fixture layout because it needs to synchronously satisfy the requirements of assembly tolerance and gravity deformation, which are calculated by finite element analysis. This paper proposes a new method to optimise fixture scheme by a non-domination sorting social radiation algorithm (NSSRA). Firstly, unfeasible nodes are eliminated by four rules according to manufacturing experiences. Afterwards, a few groups are divided based on positions of all feasible nodes. N groups are optimised using NSSRA. Finally, the best fixture layout is generated by selecting the feasible points among the optimal groups in last step. A case study of inner hood is used to illustrate the proposed method, and the results suggest that NSSRA has better efficiency and higher accuracy than NSGA-II.     

支持基于Internet的大规模定制的产品信息管理系统

基于Internet的大规模定制生产方式是一种必然趋势。在这种生产模式下,企业必须改善其结构、组织和管理方式以及产品的设计和生产方式才能适应这种模式。基于Internet的大规模定制生产的产品信息管理系统在功能和框架上与传统PDM系统不同,它有强大的协作功能,支持异构平台,有更多的功能模块。其关键技术在于分布式软件组件技术、数据该和传输过程的安全机制以及产品和零部件数量的控制策略。最后,提出了基于Internet的大规模定制条件下的产品信息管理的系统解决方案。     

A heuristic approach on the facility layout problem based on game theory

Facility layout problems are related to the location of all facilities in a plant. Numerous research works related to facility layout have been published. The applicability of these various existing models may be limited by the fact that they all ignore competitive reactions to one's actions. In addition to external competitors, some internal problems of system such as material handling system design affect layout designs. For considering these effects, some researchers have investigated multi-objective approaches that in most cases lead to the optimisation of a weighted sum of score functions. The poor practicability of such an approach is due to the difficulty of normalising these functions and quantifying the weights. To the extent that competitors do react to a firm's actions and also the facility layout problem considers several conflicting objectives by distinct decision makers in the firm, the existing models may be oversimplifications of reality. In this paper, we modelled such a facility layout problem with conflicting objectives under a duopoly Bertrand competition as a game and solved it with a proposed simulated annealing meta-heuristic. Results obtained from solving some numerical examples confirm the effectiveness of the proposed model for the layout design.     

Management optimisation based on dynamic SKU for RFID-enabled warehouse management in the steel supply chain

Radio-frequency identification (RFID) technology is one of the encouraging technologies to improve the productivity in warehouse management. However, the problem of how to explore the potential benefits of a RFID system and reduce the expenditure of RFID application are troubling many managers who are planning to, or have engaged in, the implementation. This paper enriches existing theory by introducing the useful and comprehensive warehouse management optimisation methods based on dynamic SKU (storage keeping unit) management in the design and development of a RFID-enabled warehouse. Based on the dynamic SKU management method proposed, cost optimisation methods are employed in the development of RFID-enabled warehouse. Furthermore, a storage area management optimisation for multi-size coils and a crane scheduling optimisation method is established for the purpose of enhancing the productivity of the warehouse. The optimisation methods are applied and verified in a coil warehouse and the result shows that the hardware investment is cut down by reducing the number of RFID cards used without any decrease in location accuracy and the warehouse productivity is improved significantly.