A review of function blocks for process planning and control of manufacturing equipment

Manufacturing in a job-shop environment is often characterized by a large variety of products in small batch sizes, requiring real-time monitoring for dynamic distributed decision making, and adaptive control capabilities that are able to handle, in a responsive way, different kinds of uncertainty, such as changes in demand and variations in production capability and functionality. In many manufacturing systems, traditional methods, based on offline processing performed in advance, are used. These methods are not up to the standard of handling uncertainty, in the dynamically changing environment of these manufacturing systems. Using real-time manufacturing intelligence and information to perform at a maximum level, with a minimum of unscheduled downtime, would be a more effective approach to handling the negative performance impacts of uncertainty. The objective of our research is to develop methodologies for distributed, adaptive and dynamic process planning as well as machine monitoring and control for machining and assembly operations, using event-driven function blocks. The implementation of this technology is expected to increase productivity, as well as flexibility and responsiveness in a job-shop environment. This paper, in particular, presents the current status in this field and a comprehensive overview of our research work on function block-enabled process planning and execution control of manufacturing equipment.     

A connector-based hierarchical approach to assembly sequence planning for mechanical assemblies

This paper presents an approach to find feasible and practical plans for mechanical assemblies based on a connector-based structure (CBS) hierarchy. The basic idea of the approach is to construct plans for an assembly (i.e. the root node of the CBS hierarchy) by systematically merging plans for primitive structures in the CBS hierarchy, while the plans for primitive structures are built using one of three methods: by reusing the existing plans, by retrieving the stored plans, and by geometric reasoning. The input to the approach consists of the assembly solid model, the connector-based relational model (CBRM) graph, the spatial constraint graphs, and the selected base part for the assembly, all of which are assumed to be generated previously in an interactive and/or automated way. Then, a CBS hierarchy for the assembly is automatically derived from the input CBRM by firstly establishing its functional model, which is constructed from the CBRM by decomposing the assembly or resulted part sets with respect to their connectors. Based on the CBS hierarchy, a set of assembly precedence diagrams representing good plans for the assembly are generated by merging plans for primitive structures systematically in a bottom-up manner. It can be proved that the proposed approach is both correct and complete. To verify the validness and efficiency of the approach, a variety of assemblies including some complicated products from industry are tested in the experimental CBHAP planner.     

Non-nominal path planning for robust robotic assembly

In manufacturing and assembly processes it is important, in terms of time and money, to verify the feasibility of the operations at the design stage and at early production planning. To achieve that, verification in a virtual environment is often performed by using methods such as path planning and simulation of dimensional variation. Lately, these areas have gained interest both in industry and academia, however, they are almost always treated as separate activities, leading to unnecessary tight tolerances and on-line adjustments.     

A new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems

This paper presents a new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems which is based on the idea of adaptive learning approach and simulated annealing. The proposed approach uses a weight parameter to perturb task priorities of a solution to obtain improved solutions. The weight parameters are then modified using a learning strategy. The maximization of line efficiency (i.e., the minimization of the number of stations) and the equalization of workloads among stations (i.e., the minimization of the smoothness index or the minimization of the variation of workloads) are considered as the performance criteria. In order to clarify the proposed solution methodology, a well known problem taken from literature is solved. A computational study is conducted by solving a large number of benchmark problems available in the literature to compare the performance of the proposed approach to the existing methods such as simulated annealing and genetic algorithms. Some test instances taken from literature are also solved by the proposed approach. The results of the computational study show that the proposed approach performs quite effectively. It also yields optimal solutions for all test problems within a short computational time.     

A systematic optimization approach for assembly sequence planning using Taguchi method, DOE, and BPNN

Research in assembly planning can be categorised into three types of approach: graph-based, knowledge-based and artificial intelligence approaches. The main drawbacks of the above approaches are as follows: the first is time-consuming; in the second approach it is difficult to find the optimal solution; and the third approach requires a high computing efficiency. To tackle these problems, this study develops a novel approach integrated with some graph-based heuristic working rules, robust back-propagation neural network (BPNN) engines via Taguchi method and design of experiment (DOE), and a knowledge-based engineering (KBE) system to assist the assembly engineers in promptly predicting a near-optimal assembly sequence. Three real-world examples are dedicated to evaluating the feasibility of the proposed model in terms of the differences in assembly sequences. The results show that the proposed model can efficiently generate BPNN engines, facilitate assembly sequence optimisation and allow the designers to recognise the contact relationships, assembly difficulties and assembly constraints of three-dimensional (3D) components in a virtual environment type.     

A dynamic priority-based approach to concurrent toolpath planning for multi-material layered manufacturing

This paper presents an approach to concurrent toolpath planning for multi-material layered manufacturing (MMLM) to improve the fabrication efficiency of relatively complex prototypes. The approach is based on decoupled motion planning for multiple moving objects, in which the toolpaths of a set of tools are independently planned and then coordinated to deposit materials concurrently. Relative tool positions are monitored and potential tool collisions detected at a predefined rate. When a potential collision between a pair of tools is detected, a dynamic priority scheme is applied to assign motion priorities of tools. The traverse speeds of tools along the x-axis are compared, and a higher priority is assigned to the tool at a higher traverse speed. A tool with a higher priority continues to deposit material along its original path, while the one with a lower priority gives way by pausing at a suitable point until the potential collision is eliminated. Moreover, the deposition speeds of tools can be adjusted to suit different material properties and fabrication requirements. The proposed approach has been incorporated in a multi-material virtual prototyping (MMVP) system. Digital fabrication of prototypes shows that it can substantially shorten the fabrication time of relatively complex multi-material objects. The approach can be adapted for process control of MMLM when appropriate hardware becomes available. It is expected to benefit various applications, such as advanced product manufacturing and biomedical fabrication.     

An approach to determine geometric feasibility to assembly states by intersection matrices in assembly sequence planning

In this article, an approach is described for the development of a process for the determination of geometric feasibility whose binary vector representation corresponds to assembly states. An assembly consisting of four parts is considered as an example. First, contact matrices generate the assembly's connection graph. The developing connection graph was used to model the example assembly. In the assembly's connection graph, each node corresponds to a part in the assembly, and edges in the graph of connections correspond to connecting every pair of nodes. Moreover, in the connection graph, each connection corresponds to an element in the binary vector representation. In the development of the approach, intersection matrices are used to represent interference among assembling parts during the assembly operation. Intersection matrices are defined to along the Cartesian coordinate system's six main directions. The elements of intersection matrices are constituted to Boolean values. Each element of binary vector representations includes a connection between a pair of parts. First, ordered pairs of parts are established. Then, Cartesian products, which are produced from these established ordered pairs of parts, are applied to Boolean operators. Finally, geometric feasibility of these binary vector representations is determined. In this work, some assembly systems are sampled and examined. Among these examples, six assembly sequences for a four-part packing system; two assembly sequences for a five-part shaft bearing system; 373 assembly sequences for a seven-part clutch system and assembly states have been investigated.     

A hierarchical approach on assembly sequence planning and optimal sequences analyzing

Assembly sequence planning (ASP) is a critical technology that bridges product design and realization. Deriving and fulfilling of the assembly precedence relations (APRs) are the essential points in assembly sequences reasoning. In this paper, focusing on APRs reasoning, ASP, and optimizing, a hierarchical ASP approach is proposed and its key technologies are studied systematically. APR inferring and the optimal sequences searching algorithms are designed and realized in an integrated software prototype system. The system can find out the geometric APRs correctly and completely based on the assembly CAD model. Combined with the process APRs, the geometric and engineering feasible assembly sequences can be inferred out automatically. Furthermore, an algorithm is designed by which optimal assembly sequences can be calculated out from the immense geometric and engineering feasible assembly sequences. The case study demonstrates that the approach and its algorithms may provide significant assistance in finding the optimal ASP and improving product assembling.     

A repository for design, process planning and assembly

This paper provides an introduction to the Design, Planning and Assembly Repository available through the National Institute of Standards and Technology (NIST). The goal of the Repository is to provide a publically accessible collection of 2D and 3D CAD and solid models from industry problems. In this way, research and development efforts can obtain and share examples, focus on benchmarks, and identify areas of research need. The Repository is available through the World Wide Web at URL http://www.parts.nist.gov/parts.     

Tool selection-embedded optimal assembly planning in a dynamic manufacturing environment

This paper presents an approach for tool selection-embedded optimal assembly planning in dynamic manufacturing environments. It aims to embed assembly tools into the planning process of assembly sequences in a dynamic shop-floor. The experimental results demonstrate that the developed approach is efficient and practical for a high fidelity assembly sequence with alternatives of assembly-tool sets. The dynamic assembly planning can efficiently support product assembly by generating feasible assembly sequences. It provides an effective design-aiding tool to virtually deal with various what-if scenarios regarding product assembly. In particular, the Web-based application developed in this research can be incorporated into a high-performance design and manufacturing environment on the Web, forming a distributed, collaborative and globally networked tool for product assembly planning.     

A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing

Radio frequency identification (RFID) technology has been used in manufacturing industries to create a RFID-enabled ubiquitous environment, in where ultimate real-time advanced production planning and scheduling (APPS) will be achieved with the goal of collective intelligence. A particular focus has been placed upon using the vast amount of RFID production shop floor data to obtain more precise and reasonable estimates of APPS parameters such as the arrival of customer orders and standard operation times (SOTs). The resulting APPS model is based on hierarchical production decision-making principle to formulate planning and scheduling levels. A RFID-event driven mechanism is adopted to integrate these two levels for collective intelligence. A heuristic approach using a set of rules is utilized to solve the problem. The model is tested through four dimensions, including the impact of rule sequences on decisions, evaluation of released strategy to control the amount of production order from planning to scheduling, comparison with another model and practical operations, as well as model robustness. Two key findings are observed. First, release strategy based on the RFID-enabled real-time information is efficient and effective to reduce the total tardiness by 44.46% averagely. Second, it is observed that the model has the immune ability on disturbances like defects. However, as the increasing of the problem size, the model robustness against emergency orders becomes weak; while, the resistance to machine breakdown is strong oppositely. Findings and observations are summarized into a number of managerial implications for guiding associated end-users for purchasing collective intelligence in practice.     

A hybrid-graph approach for automated setup planning in CAPP

In this paper, a systematic approach for automated setup planning in CAPP is introduced. The concept of “hybrid graph”, which can be transferred into directed graph by changing any two-way edge into one-way edge, is introduced. The specified graph theory is effectively used in setup planning. Tolerance relations are used as critical constraints for setup planning. Comprehensive principles are explored and summarized for setup planning. The hybrid-graph theory, accompanied by matrix theory, is used to aid computerizing these principles. An example is illustrated to demonstrate the algorithm.     

Chaotic particle swarm optimization for assembly sequence planning

Assembly sequence planning of complex products is difficult to be tackled, because the size of the search space of assembly sequences is exponentially proportional to the number of parts or components of the products. Contrasted with the conventional methods, the intelligent optimization algorithms display their predominance in escaping from the vexatious trap. This paper proposes a chaotic particle swarm optimization (CPSO) approach to generate the optimal or near-optimal assembly sequences of products. Six kinds of assembly process constraints affecting the assembly cost are concerned and clarified at first. Then, the optimization model of assembly sequences is presented. The mapping rules between the optimization model and the traditional PSO model are given. The variable velocity in the traditional PSO algorithm is changed to the velocity operator (vo) which is used to rearrange the parts in the assembly sequences to generate the optimal or near-optimal assembly sequences. To improve the quality of the optimal assembly sequence and increase the convergence rate of the traditional PSO algorithm, the chaos method is proposed to provide the preferable assembly sequences of each particle in the current optimization time step. Then, the preferable assembly sequences are considered as the seeds to generate the optimal or near-optimal assembly sequences utilizing the traditional PSO algorithm. The proposed method is validated with an illustrative example and the results are compared with those obtained using the traditional PSO algorithm under the same assembly process constraints.     

A spatiotemporal information management framework for product design and assembly process planning reconciliation

This paper introduces an innovative framework for product design and assembly process planning reconciliation. Nowadays, both product lifecycle phases are quasi concurrently performed in industry and this configuration has led to competitive gains in efficiency and flexibility by improving designers’ awareness and product quality. Despite these efforts, some limitations/barriers are still encountered regarding the lack of dynamical representation, information consistency and information flow continuity. It is due to the inherent nature of the information created and managed in both phases and the lack of interoperability between the related information systems. Product design and assembly process planning phases actually generate heterogeneous information, since the first one describes all information related to “what to be delivered” and the latter rationalises all information with regards to “how to be assembled”. In other words, the integration of assembly planning issue in product design requires reconciliation means with appropriate relationships of the architectural product definition in space with its assembly sequence in terms of time. Therefore, the main objective is to provide a spatiotemporal information management framework based on a strong semantic and logical foundation in product lifecycle management (PLM) systems, increasing therefore actors’ awareness, flexibility and efficiency with a better abstraction of the physical reality and appropriate information management procedures. A case study is presented to illustrate the relevance of the proposed framework and its hub-based implementation within PLM systems.     

RFID-enabled real-time wireless manufacturing for adaptive assembly planning and control

Wireless Manufacturing (WM) is emerging as a next-generation advanced manufacturing technology (AMT). WM relies substantially on wireless devices (e.g. RFID—Radio Frequency Identification or Auto ID—Automatic Identification, and on wireless information/communication networks (e.g. Wi-Fi and Bluetooth), for the collection and synchronization of manufacturing data. This paper proposes a WM framework where RFID devices are deployed to workstations, critical tools, key components, and containers of WIP (Work In Progress) materials to turn them into so-called smart objects. The study is based on a simplified product assembly line. Smart objects are tracked and traced and shop-floor disturbances are detected and fed back to decision makers on a real-time basis. Such real-time visibility closes the loop of adaptive assembly planning and control. A facility called assembly line explorer is provided for the line manager to oversee the status of the entire assembly line, and a workstation explorer facility for operators to monitor the status of their operations at corresponding workstations. These facilities improve the effectiveness of managerial decisions and operational efficiency.     

An assembly oriented design framework for product structure engineering and assembly sequence planning

The paper describes a novel framework for an assembly-oriented design (AOD) approach as a new functional product lifecycle management (PLM) strategy, by considering product design and assembly sequence planning phases concurrently. Integration issues of product life cycle into the product development process have received much attention over the last two decades, especially at the detailed design stage. The main objective of the research is to define assembly sequence into preliminary design stages by introducing and applying assembly process knowledge in order to provide an assembly context knowledge to support life-oriented product development process, particularly for product structuring. The proposed framework highlights a novel algorithm based on a mathematical model integrating boundary conditions related to DFA rules, engineering decisions for assembly sequence and the product structure definition. This framework has been implemented in a new system called PEGASUS considered as an AOD module for a PLM system. A case study of applying the framework to a catalytic-converter and diesel particulate filter sub-system, belonging to an exhaust system from an industrial automotive supplier, is introduced to illustrate the efficiency of the proposed AOD methodology.     

Automatic assembly path planning for wiring harness installations

The automotive industry of today is becoming more focused on electrified and hybrid solutions, where both conventional combustion engines and battery supplied electrical engines need to fit in an already densely packed vehicle. Many quality problems are related do flexible parts. In particular, the assembly of electric cables and wiring harnesses is difficult due to its concealed routing, multiple branching points, weights and the flexibility in the material. To avoid late detection of assembly problems, the assembly aspect must be considered early during conceptual design and production preparation with respect to both feasibility and ergonomics. Development of automatic path planning methods in virtual manufacturing tools supporting deformable parts is therefore highly motivated.     

A practical approach to a process planning expert system for manufacturing processes

In this paper the methodical techniques applied by the human process planning expertise is simulated. It considers the process plans design, or process selection. Software modules are designed to generate a process plan or several plans for a new part according to the input data from its engineering drawing. A specific module for each surface type, to match the surface parametric data and the required quantities with respect to the capability matrices, in order to locate the most eligible process plan is identified and used.