Multi-plant assembly planning models for a collaborative manufacturing environment

In a global supply chain, the components or parts of a product may be distributed and produced at various plants in a collaborative way for the purpose of expanding capacity and reducing costs. For an assembled product, the assembly operations for assembling the product may be performed at different assembly plants at various geographical locations. Therefore, in this collaborative manufacturing environment, it is required that one develops a multi-plant assembly planning model for organizing and distributing the assembly operations to the suitable plants for completing the final product. In this research, a multi-plant assembly planning model for generating and evaluating the multi-plant assembly sequences is presented. New graph-based models are developed to model and generate the assembly sequences. The feasible assembly sequences are analysed and evaluated based on several cost objectives. The multi-plant assembly planning model is formulated with the aim of minimizing the total of assembly costs and multi-plant costs. As a result, the optimized multi-plant assembly sequences can be obtained and each of the assembly operations is assigned to the suitable plant with a minimized cost. Example parts are tested and discussed.     

Integrating assembly and machining planning using graph-based representation models

Traditionally, assembly planning and machining planning are considered as two independent tasks. In assembly planning, the components to be sequenced are considered as machined and finished. In machining planning, the focus has been on machining each individual component. In previous research, machining and assembly planning are analysed separately. However, in order to achieve some design specifications, the assembly and machining operations may need to be mixed in an integrated sequence. For example, a machining operation may need to be performed on a subassembly formed by a group of components in order to complete certain geometric features. In other cases, an assembly operation cannot be performed unless certain geometric features are completely machined. Therefore, the assembly and machining operations need to be planned in a combined sequence. In this research, new graph-based representation models were developed to integrate assembly and machining planning. First, an assembly-machining operation graph was developed to represent the spatial relationships between the components as well as to express the operational precedence of the machining and assembly operations. Next, the integrated assembly and machining sequences were generated using a tree structure called the assemblymachining sequence tree. Using the graph-based methodology, all the feasible integrated assembly and machining sequences can be generated and evaluated. The main objective is to provide a complete model for integrating assembly and machining sequences. A combined evaluation can be performed to find the best sequence based on certain time and cost objectives. The presented methodology is implemented on a personal computer and several example parts are discussed.     

Liaison concatenation – A method to obtain feasible assembly sequences from 3D-CAD product

Selection of optimized assembly sequence from the available feasible assembly sequences is significantly essential to achieve cost-effective manufacturing process. To achieve this, at the outset, generation of feasible assembly sequences with topological, geometrical, precedence and stability conditions should be generated. The increase of part count in a product results huge number of assembly sequences, the Liaison matrix/Liaison graph generated based on the connections between the assembly components eliminates non-possible assembly sequences at the initial phase. There exist methods namely cut-set method to eliminate the non-possible assembly sequences using liaison graph. In this paper a new approach to eliminate the non-possible assembly sequences based on liaisons is described and the correctness of the methodology is illustrated with an example. The methodology to obtain the feasible assembly sequences is also briefly described and presented. An algorithm to interface with the CAD environment is described briefly.     

Optimisation of assembly sequences for compliant body assemblies

Multi-sequence modelling is proposed to optimise assembly sequences for compliant body assemblies such as automotive and aircraft bodies. Multi-sequence modelling is composed of assembly modelling, assembly sequences, tolerance analysis, and assembly operations. Assembly modelling describes the geometric modelling through the liaison graph, which is based on assembly sequence optimisation. Assembly sequences provide information for assembly sequence optimisation. Three-dimensional tolerance analysis is employed to evaluate assembly operations, which is different from previous conceptual tolerance analysis. A genetic algorithm is presented to optimise assembly operations among components. Results show that different sequences lead to a different tolerance of key product characteristics because assembly operations among components are not identical. This paper provides the flowchart of optimising assembly sequences according to the tolerance of key product characteristics.     

Design and optimisation of assembly technique for auto-body components

The dimensional quality of auto-body relates to the whole external appearance, wind noise, the effect of closing the door and even driving smoothness of vehicles. The assembly dimensional quality can be improved by optimising assembly operations between parts and reasonable allocating tolerances of components. A multi-attribute directed liaison graph is proposed to describe precedence relationships and key control characteristics (KCCs) to eliminate unfeasible assembly sequences. A hybrid particle swarm optimisation and genetic algorithm is presented to optimise assembly operations for selecting the best assembly sequence. Based on the above, tolerances of the optimal KCCs are designed by using NSGA-II algorithm according to assembly tolerances and manufacturing costs. To improve optimisation effectiveness, the initial population uses the orthogonal experimental design and sensitivity coefficients of KCCs to generate chromosomes. Finally, the work applied the method by illustrating the process of assembly sequence optimisation and tolerance allocation, and the results show that this case verified the proposed method.     

3D geometric constraint analysis and its application on the spatial assembly sequence planning

Focusing on the spatial geometric feasible assembly sequence planning and optimising, a novel approach entitled 3D-GCA is proposed based on the method of Geometric Constraint Analysis (GCA) incorporated with the Oriental Bounding Box (OBB) and Separation Axis Theory. Accordingly, the corresponding computer-aided 3D assembly sequence planning system is developed and two cases are studied in detail. The analysis results demonstrate that, with 3D-GCA method, the spatial assembly precedence relations (APRs) can be calculated out correctly and completely. Thereby, all the 3D geometric feasible assembly sequences can be derived automatically. Moreover, an optimisation algorithm is designed based on 3D-GCA method, by which, the optimal assembly sequences can be calculated out according to two criteria, e.g., assembly angle and assembly direction. The 3D-GCA method and its algorithms can provide significant assistance in the spatial geometric feasible assembly sequences reasoning and the optimal sequences selection.     

基于petri网装配序列灰色聚类决策研究

利用petri网直观图形化特点建立装配模型,并根据petri网原理得出可行装配序列。影响可行装配序列的大部分因素是定性的、模糊的、非数值的,将装配序列看作灰色系统,采用灰色聚类决策方法对可行序列进行评估。分析了影响因素的灰色分类并且研究了灰色聚类决策步骤。实例分析表明,该方法为petri网原理所得可行序列进行正确的评估并且得出决策向量。     

Optimal disassembly of complex products

This paper presents a method for determining the optimum disassembly sequence for selective disassembly of discarded complex products. This methodology has been developed within the framework of the increasing need for formulation of a theory on selective disassembly and the various purposes of it. The objective of the optimization is maximizing the economic performance of the disassembly process within given technical and environmental constraints. It is demonstrated that the method, that is based on graphs, can be used to generate optimum sequences according to various objectives in a straightforward way. Also a ranking of the most favourable alternative sequence is possible. This is important to the inclusion of other criteria in the model and in adaptation of the disassembly system to fluctuating parameters like material yields and constraints. Contrary to earlier work on generation of disassembly sequences, in selective disassembly all possible incomplete disassembly sequences are included. This considerably increases the number of disassembly sequences to be studied with respect to the number of possible assembly sequences. According to the method described here, the number of viable sequences is determined in a straightforward way. On the basis of a specific example the general methodology is discussed.     

A Bayesian network approach for fixture fault diagnosis in launch of the assembly process

Verification and correction of faults related to tooling design and tooling installation are important in the auto body assembly process launch. This paper introduces a Bayesian network (BN) approach for quick detection and localisation of assembly fixture faults based on the complete measurement data set. Optimal sensor placement for effective diagnosis of multiple faults, structure learning of the Bayesian network and the diagnostic procedure are incorporated in the proposed approach. The effective independence sensor placement method is used to reach the desired number of optimal sensor locations, which provide the concise and effective sensor nodes to build the diagnostic Bayesian network. A new algorithm based on conditional mutual information tests is put forward to learn the Bayesian network structure. The body side assembly case was used to illustrate the suggested method and the simulation analysis was performed to evaluate the effectiveness of the diagnostic network. The work demonstrated that the proposed methodology composes a feasible and powerful tool for fixture fault diagnosis in launch of the assembly process.     

Process and production planning for circuit board assembly

Process planning output can be post-processed into criteria for job scheduling decisions in printed circuit board assembly using surface-mount technology (SMT). Artificial intelligence-based techniques used in computerized planning and scheduling systems in other industries can be extended to printed circuit board operations. These techniques include blackboard architectures, object-oriented programming systems, and nonmonotonic reasoning systems. These techniques were used to demonstrate a unique architecture of blackboard systems that communicate via object-oriented messages to arrive at a shop-floor process plan and production schedule. The methodology was specialized to the assembly of printed circuit boards using surface-mounted components in a high-variety/low-volume product mix. The assembly facility was represented as a hierarchical object of product, process, and organizational knowledge. The system of working heuristics was integrated within a prototype environment with the practitioners that assisted in its development. The end result is a good working methodology for system development, implementation, and maintenance by knowledge worker involvement.     

Control logic verification for an automotive body assembly line using simulation

In this paper, an approach is proposed that verifies the controller logic processes for the automobile industry via simulation. For this purpose, a state-based object model that creates a virtual car body assembly line is proposed and a verification methodology using observed signal sequences during the simulation is proposed. This approach was applied to an assembly line controlled by a PLC and the effectiveness of the proposed system was explained in a case study.     

Design for global manufacturing and assembly

In this paper the author presents and tests new concurrent engineering strategies that focus on manufacturing and assembly operations with a global perspective. Specifically, the focus is upon new design for manufacturability and assembly (DFMA) strategies to support multi-facility, global operations. These DFMA strategies are more holistic than most published techniques in that they focus on total system approaches that explicitly consider product mix, process configuration, and capital procurement strategies, as well as tooling, design, and set-up costs associated with manufacture and assembly. Furthermore, the DFMA strategies presented here consider the cost of transportation logistics in multi-facility, global manufacturing, assembly, and distribution networks., A general mathematical formulation is presented and tested under realistic conditions. It is demonstrated that this model can be used for capacity planning and product sourcing for multiple part types in many facilities. Similarly, it can be used to examine the sensitivity of solutions to changes in various costs, productivity levels, or product configuration and mix assumptions at each facility. Test results demonstrate the efficacy of use of the formulation in general terms. Finally, a research agenda is posited for the future development of the strategies.     

Assembly systems layout design model for delayed products differentiation

Frequently changing customers’ needs and market pressures motivate manufacturers to offer a wide variety of their products. Poor demand prediction and increased manufacturing complexities and managerial burdens are just a few symptoms of products variety proliferation. Applying a postponement strategy is an effective method for mitigating the complexities arising due to increased products variety and customisation. Delayed product differentiation (DPD) is a prerequisite for applying form postponement strategies, where the unique features that distinguish each product are added at the final stages of production. This paper introduces an innovative design methodology to derive and represent an assembly line schematic layout for delayed products differentiation. The proposed methodology incorporates product commonality analysis and feasible assembly sequences to synthesise the assembly line layout in a single integrated logical design framework, without pre-defining either the number or the positions of differentiation points along the line. Products commonality analysis is performed using cladistics techniques commonly used for biological classification. The classical cladistics was modified to take into consideration the precedence constraints, which are required to ensure the feasibility of assembly sequences. Real product variants are used to validate the proposed DPD assembly line layout design methodology and demonstrate its merits.     

Optimization of the assignment of circuit cards to assembly lines in electronics assembly

Process planning is an important and integral function for ensuring efficient operations in printed circuit card assembly systems. This paper presents a new approach for solving the circuit card to assembly line assignment problem to minimize assembly time. This problem occurs frequently in process planning for electronic assembly systems and involves considering other interelated process planning problems. The line assignment problem is formulated as a large-scale mixed-integer programming problem and then solved using problem decomposition along with the branch-and-bound algorithm. Techniques for improving the solution time are discussed, and the solution approach is demonstrated using industry representative data sets from Lucent Technologies. For the data sets considered, the solution approach provides solutions within 3% of optimal in approximately 6 min of computation time on a Sun UltraSparc 2 Workstation. The solution approach developed for addressing the line assignment problem can serve as a useful decision-support tool by offering significant opportunities to improve the productivity and throughput of the assembly lines with improved process plans. The approach also allows planning engineers to respond faster to changes in production requirements. This research will be of interest to researchers in printed circuit card assembly systems and to practitioners in both original equipment manufacturing and contract assembly firms.     

A review of the support tools for the process of assembly method selection and assembly planning

This paper reviews the substantial body of research into software and other tools to support the closely related methodologies of assembly system selection, design for assembly, and assembly planning. Reported research has led to the adoption of a number of tools in current use in manufacturing industry. Here, the scope of this research, and its practical applications, is considered with a view to identifying the application domain of each approach and support tool. The authors are led to the conclusion that there is a need for further research into a methodology for the initial selection of the assembly method (e.g. assembly line, fixed point assembly, etc), and that such a methodology should consider not only factors of product technology, but also the industrial environment where assembly is to take place. Further, a knowledge-based decision support tool could facilitate the application of this methodology, and expand decision support further into the selection of assembly planning methods for subsequent application.     

Using constraint-satisfaction to optimise disassembly sequences generated from AND/OR information

This paper applies a constraint-based method, shown to successfully find the optimal order of component removal using precedence information, to finding the optimal sequence via AND/OR data. Development of disassembly theory is vital for practically all product end-of-life strategies. In particular, Disassembly Process Plans (DPPs) allow the careful selection and removal of components for recycling and reuse. While AND/OR graphs explicitly embody all of the feasible DPPs of an assembly, generating the best plan is non-trivial due to the rapid increase in the number of solution paths. In contrast, defining the physical restrictions between the components using precedence relationships is implicit and hence compact. By converting AND/OR representations into precedence ones, not only is the size of the problem reduced, modified techniques developed previously are applicable. Dependent upon the structure of the subassemblies, two different approaches are used to achieve this: the introduction of dummy components, and by means of the set of operations upon the subassemblies. Thus an all-encompassing methodology is created that can deal with any DPP representation such that the optimal sequences may be found.     

Generating complete disassembly sequences by utilising two-dimensional views

This research work proposes a novel method to generate the complete disassembly sequences for mechanical products by utilising the part interference matrix which contains the removal directions of the parts and the part connection graph which indicates the contact among the parts in the assembly. Contrary to the earlier methods, the proposed method considers the two-dimensional views generated from the computer-aided design assembly model for automatically identifying the part removal directions and for generating the part connection graph. Rules are formulated in the proposed method to identify the part removal directions effectively and also to reduce the size of part connection graph, since the method of identifying the part removal directions and the size of the formulated graph plays a vital role in the generation of disassembly sequence. Finally, a heuristic method is developed to generate the best feasible disassembly sequences. The effectiveness of the approach is illustrated with three examples.     

Integrating nanowires with substrates using directed assembly and nanoscale soldering

This paper describes a new methodology for integrating nanowires with micropatterned substrates using directed assembly and nanoscale soldering. Nanowires containing ferromagnetic nickel segments were fabricated by electrodeposition in nanoporous membranes. The nanowires were released by dissolution of the membrane and subsequently aligned relative to micropatterned substrates using magnetic field-directed assembly. After assembly, the wires were permanently bonded to the substrates using solder reflow to form low-resistance electrical contacts. This is the first demonstration of the use of nanoscale solder reflow to form low-resistance electrical interconnects between nanowires and substrates, and we demonstrated the utility of the strategy by fabricating a nanowire-based functional analog integrator.     

PCB assembly scheduling for collect-and-place machines using genetic algorithms

In printed circuit board (PCB) assembly, collect-and-place machines, which use a revolver-type placement head to mount electronic components onto the board, represent one of the most popular types of assembly machinery. The assignment of feeders to slots in the component magazine and the sequencing of the placement operations are the main optimisation problems for scheduling the operations of an automated placement machine. In this paper, we present different genetic algorithms (GAs) for simultaneously solving these highly interrelated problems for collect-and-place machines in PCB assembly. First we consider single-gantry machines as the basic type of machinery. In the conventional GA approach all placement operations and the feeder-slot assignment are represented by a single chromosome. In order to increase the efficiency of the genetic operators, we present a novel GA approach, which integrates a clustering algorithm for generating sub-sections of the PCB and grouping the corresponding placement operations. It is shown that the proposed GAs can be extended to schedule dual-gantry placement machines, which are equipped with two independent placement heads and two dedicated component magazines. Hence, component feeders have to be allocated between the two magazines. To solve this allocation problem, two different heuristic strategies are proposed. Finally, detailed numerical experiments are carried out to evaluate the performances of the proposed GAs.     

A function block based approach for increasing adaptability of assembly planning and control

Today's market turbulences cause frequent changes in manufacturing environments. Products diversity, small batch sizes and short life cycles have increased production uncertainties and created a highly dynamic shop floor environment. One essential requirement of such an environment is an adaptive planning and control system that is sufficiently agile to respond to the variety of production requirements and enable easy system reconfiguration at run-time. When developing a product, assembly is a key area that impacts the manufacturing system's responsiveness to the changes. In this research, a framework and a new methodology are introduced to increase the adaptability and autonomy of job-shop assembly process planning and control using function blocks (FBs). A function block is a reusable functional module with an explicit event-driven model, and provides for data flow and finite state automata based control. Event-driven and FB-enabled decision-making is unique in adaptive assembly planning and control. It is explained through an example of a two-robot assembly work cell, where the result of the adaptive planning is wrapped in FBs for execution. The proposed approach has been implemented and simulated using Matlab Simulink in the case study. The simulation demonstrates how this approach would increase the adaptability and responsiveness to changes that may occur regularly in dynamic job-shop assembly operations.