A UML-based approach for the development of shop floor control systems

As a key part of computer integrated manufacturing (CIM), shop floor control systems (SFCS) play an essential role in the effective operations of a shop floor. The development of SFCSs is an extremely complex process, given the requirements for synchronisation and coordination. Object-oriented methods offer a promising solution to develop a reusable, maintainable and interoperable SFCS. However, current O-O practices for developing SFCSs are hindered by proprietary representations, which may lead to problems with the portability and interoperability of models. UML, as an industrial standard for O-O notations, has been widely accepted by practitioners to describe static and dynamic parts of a complex system. From the perspective of software engineering, UML offers a variety of standard notations to support the full life-cycle of system development. In this paper, an approach to developing an SFCS using UML through analysis, design and implementation phases is presented, based on the three level hierarchical architecture. An example workstation is studied as an illustration to clarify the proposed approach. In addition to the reusability, portability and maintainability, the presented UML-based development enhances the efficiencies and qualities of SFCS development, considering a wide range of mature tool supports (such as Rational Rose) for UML are available.     

Economic analysis of inventory systems: a reply

A shop floor control system (SFCS) consisting of three hierarchical control levels (shop, workstation, and equipment) is described. Each controller plans, schedules, and executes the activities necessary to process an order. An intelligent workstation controller (IWC), which is a part of the SFCS, is described in detail. The 1WC receives information such as part type and quantity, part routeing specifications, and process plans from the shop level controller and coordinates production activities. The IWC performs three main functions—planning, scheduling, and execution in real-time in order to ensure completion of jobs assigned by the shop controller. The focus of this paper is to develop a robust adaptive scheduler to support the IWC which fits within the functional SFCS architecture. The objectives of this paper are: (1) to develop a neural network model that generates several part dispatching strategies based on workstation status; (2) to develop a mutti-pass simulator that evaluates the generated strategies and selects the best strategy to maximize system efficiency; and (3) to compare the efficiency of the scheduling function with other single-pass strategies with respect to several performance criteria.     

MANPro: mobile agent-based negotiation process for distributed intelligent manufacturing

This paper examines negotiation procedures in an agent-based distributed shop floor control system (SFCS). A distributed SFCS is under a heterogeneous environment, which is controlled through negotiations between autonomous agents. The negotiation-based control can be considered as the core of a distributed control paradigm. An efficient information exchanging mechanism and an information model with reasonable structure are indispensable for effective negotiations. This paper proposes a novel negotiation mechanism, called a mobile agent-based negotiation process (MANPro), which applies a mobile agent system to the process of information exchange. Since using mobile agents allows each component to execute asynchronously and autonomously and to adapt dynamically to the execution environment, MANPro may guarantee autonomy of agents. Moreover, it is possible to build a fully distributed and autonomous SFCS by using MANPro. MANPro is based on the agent-based control architecture, which includes a communication architecture and an information architecture. The communication architecture provides the exchanging mechanism of information, defining functional modules to support the mechanism while the information architecture provides the framework for information modelling on negotiation, proposing information models required for introducing the ontology concept.     

A conceptual framework for the generation of simulation models from process plans and resource configuration

Although simulation is a popular tool for modelling and analysing modern manufacturing systems, to model shop floor control systems (SFCSs) in simulation requires quite costly efforts, since they are responsible for resolving various decision problems, such as deadlock, part dispatching, and resource conflict. The objective of the paper is to address a conceptual framework necessary to generate a WITNESS simulation model automatically from graph-based process plans and resource configurations. A graph-based process plan is used to capture part operations, their related resource requirements, and their temporal precedence relationships. A WITNESS simulation model is a graphical representation of shop floor resources with the part flow logic embedded within each resource element. To generate a WITNESS model, a process plan is automatically converted into a machine-centred part routeing graph (MCPRG) and then a transport-tending part routeing graph (TTPRG). The MCPRG implies part flows among machines, in which a node represents a machine and an edge represents a part route. The TTPRG implies part flows among machines and material handling devices, in which a node represents either machine or material handler, and an edge represents a part route. From the TTPRG, the part's input and output rules for each resource can be automatically extracted and plugged into the WITNESS model. The approach proposed in the paper enables manufacturers to generate a simulation model rapidly and effectively for performance measurement, such as bottleneck identification, work in progress, throughput times, dynamic resource utilization, and deadlock, of the SFCSs.     

Adaptive and dynamic process planning using neural networks

Although feature-based process planning plays a vital role in automating and integrating design and manufacturing for efficient production, its off-line properties prevent the shop floor controller from rapidly coping with dynamic shop floor status such as unexpected production errors and rush orders. This paper proposes a conceptual framework of the adaptive and dynamic process planning system that can rapidly and dynamically generate the needed process plans based on shop floor status. In particular, the generic schemes for constructing dynamic planning models are suggested. The dynamic planning models are constructed as neural network forms, and then embedded into each process feature in the process plan. The shop floor controller will execute them to determine machine, cutting tools, cutting parameters, tool paths and NC codes just before the associated process feature is machined. The dynamic nature of process planning enables the shop floor controller to increase flexibility and efficiency in unexpected situations.     

A formal structure and implementation of a robotic material handling controller in an automated shop floor environment

This paper proposes a formal structure and framework for a robotic material handling (MH) equipment-level controller in a hierarchical shop floor control architecture. This framework essentially attempts to integrate shop-level process planning with material handling at the workplace. Handling operations are therefore integrated with manufacturing functions in order to ensure 'seamless' material transfer and processing. The responsibilities of the MH equipment controller include: interface with a MH robot; read and interpret handling plans from a database (in the form of an AND/OR graph); plan and schedule MH activities; perform path planning and grasp planning for the required task; generate generic robot-level commands automatically; and convert generic robot-level commands to robot-specific instructions. A MH equipment-level controller has been designed and implemented for a PUMA 560 robot in the CIM lab at the Pennsylvania State University. The proposed controller can work for various situations and job volumes. In addition, by creating the framework described in this paper, extending the concept for other parts and obstacles with various features, coordinating the vision system or the CAD system to the proposed controller, and combining complete path planning and grasp planning systems, a fully operational MH equipment-level controller can be realized.     

Bid generation and evaluation for MANPro-based real time scheduling

This paper proposes a bid generation and evaluation scheme and an information model for real-time scheduling. It is well known that an agent-based control approach performs according to both the negotiation mechanism itself and the single agent internal strategic policies. Mobile agent-based negotiation process (MANPro), which has been proposed in our previous work, concerns the first issue of the negotiation mechanism. This paper concerns the second issue of the single agent internal strategic policies. It explains how bids are generated and evaluated and how agents obtain mutual agreement in MANPro. First, the generic bid generation and evaluation framework for MANPro-based negotiation is proposed. Then, the generic framework is applied to a real-time scheduling system for a distributed shop floor control system (SFCS).     

Function block design for adaptive execution control of job shop machining operations

Small volume and high product mix contribute greatly to the complexity of job shop operations. In addition, shop floor uncertainty or fluctuation is another issue regularly challenging manufacturing companies, including job delay, urgent job insertion, fixture shortage, missing tools, and even machine breakdown. Targeting the uncertainty, we propose a function block-based approach to generating adaptive process plans. Enabled by the function blocks, a so-generated process plan is responsive and tolerant to an unpredictable change. This paper presents in detail how a function block is designed and what it can do during process plan execution. It is expected that this new approach can largely enhance the dynamism of fluctuating job shop operations.     

Elaboration and validation of AND/OR graph-based non-linear process plans for shop floor control

Feature-based process planning has been popular in academia and industry owing to its ability rigorously to integrate design and manufacturing. In spite of this benefit, feature-based process planning has been difficult to implement because it is not easy to extract even simple features from the design data automatically and efficiently. Furthermore, it is even more difficult to construct the temporal precedence relationships among the extracted features with regard to plan alternatives and sequence options. The objective here is to present elaboration and validation methodologies for AND/OR graph-based non-linear process plans that help users construct, validate or modify a controller-friendly process plan easily and efficiently. An elaborated process plan created by a CAPP or an experienced process planner should be validated with respect to various validation criteria, such as the shape of a finished part, feature interaction, feature interference, feature manufacturability and flexibility for shop floor control. For each validation criteria, the invalid indicator matrix proposed here can quantify the degree of invalidity of the process plan. The invalid indicator matrix will help the process planner fix and refine rapidly the elaborated process plan. The methodologies proposed will save cost and time in the production of a controller-friendly process plan. Initial results are promising.     

A GLOBAL FLOOR PLANNING TECHNIQUE FOR VLSI LAYOUT

Over the years, many CAD tools for VLSI macrocelf design have become available that automatically perform some of the physical synthesis phases to reduce development costs. Although floor planning imposes global constraints on the quality of the final layout, state-of-the-art tools do not completely support floor planning synthesis. A new floor planning method for macrocell layout style is presented. The floor plan state space is characterized by an equivalence relation to apply efficient solution techniques. A new pseudo-polynomial area optimization algorithm is proposed that derives from a given hierarchical floor plan tree the optimal slicing tree. The order of this floor plan tree is at least 2 and at most 5. Extensions of this approach to cover non-slicing floor plans are also described. Since floor planning and routing are interdependent tasks, an improved dynamic updating scheme is proposed to consider the interconnection area around each cell during the floor plan assembly. The method has been successfully applied to an industrial design with about 260,000 transistors.     

Generating daily production plans for complex manufacturing facilities using multi-objective genetic algorithms

Modern production tracking and planning systems produce good inventory plans. Unfortunately, daily production problems often produce an inventory profile that is significantly different from that of the production plan. Several manufacturing objectives are available to remedy inventory profile problems, but a weighted combination of them can be more effective. We propose using genetic algorithms to search for best weight assignments in multi-objective daily production planning problems. This approach takes snapshots of a factory's inventory, equipment capacity and demands to generate a near optimal shop floor daily production plan. The implemented system runs on a daily basis at midnight for 40 min and generates the following day's production plan. Tests of this system in a large-scale semiconductor manufacturing facility show the proposed approach generates production plans of high quality in reasonable run times under many factory conditions.     

Event-driven multi-agent ubiquitous manufacturing execution platform for shop floor work-in-progress management

It has been reported that radio frequency identification (RFID) technology is applied to manufacturing shop floors for capturing and collecting real-time field data. Real-time information visibility and traceability allows decision makers to make better-informed shop floor decisions. It has been a great challenge to process a huge amount of RFID data into useful information for managerial uses. This paper presents an event-driven shop floor work-in-progress (WIP) management platform for creating a ubiquitous manufacturing (UM) environment. The platform aims to monitor and control dynamic production and material handling through RFID-enabled traceability and visibility of shop floor manufacturing processes. The platform provides facilities to process shop floor real-time RFID events and to aggregate actionable and meaningful operational information to support decision-making activities. An information processing mechanism based on a critical event model is proposed to organise real-time field data in various abstract levels for enterprise decisions. A case study at an air conditioner manufacturing company is used to demonstrate how the proposed platform can benefit its shop floor WIP management by showing how production and logistic operators and their supervisors accomplish their tasks.     

Material requirements planning in hierarchical production planning systems

Material requirements planning (MRP) is a way to develop the time phased material and other resource requirements to satisfy the needs of a master production schedule. Hierarchical production planning (HPP) is a framework for analysis and decision making in complex production environments. They are complementary approaches to the decision support system needs of multi-stage production systems. The hierarchical approach provides for efficient management review of proposed plans at corporate, plant, and shop levels while MRP provides a sound and detailed basis for understanding the implications of proposed plans and for executing the selected plan. The relationships between these two approaches are illustrated with an example application.     

A knowledge based approach for automatic process plan generation in an electronic assembly environment

In this paper important issues in the automatic generation of process plans are addressed. Since the conventional method of electronic assembly planning is subjective and depends greatly on the skills, memory, knowledge, and experience of the planners, inconsistencies in the plan arise, which in turn create problems in the manufacturing environment. An automatic electronic assembly planning system that would offer advantages over manual systems has been implemented. Due to frequent advances in technology, the electronic industry is a very dynamic one. This affects the effectiveness of the current process plans and the applicability of the system that generates them. The framework of a system which takes into account the dynamic nature of the environment is presented as an example. A network representation of plans that allows for flexibility and modularity in the planning system is being used. A hybrid architecture consisting of production rules, procedural algorithms and a hierarchical database has been implemented using an expert system shell.     

Work-in-process clearing in supply chain operations planning

In this study we provide insights into the effectiveness of the clearing function concept in a hierarchical planning context. The clearing function is a mathematical representation of the relation between the Work-In-Process (WIP) and the throughput of a production process. We use it in a deterministic order release planning model to anticipate the dynamics of the operational level, which is subject to uncertainties. A multi-period single-item order release and scheduling problem is considered in which the delivery schedule of the orders is determined through the planned lead times, and the capacity loading decisions are separated from the order release decisions in a way so as to plan for on-time deliveries. Early or late delivery of the orders, which are released and delivered in batches, has not been considered explicitly in previous studies on clearing functions, and it significantly affects the inventory costs. Both linear and non-linear clearing functions are tested using a simulation approach. The results indicate that modeling the clearing of WIP by a shop should be based on the short-term operational dynamics of the shop rather than on the long-term average shop behavior, since it improves the consistency between the operational planning and scheduling levels of the hierarchy. The presented methods and results provide valuable information on modeling production characteristics in aggregate production planning and scheduling models.     

The design of a line control system for the modular furniture industry

This paper describes the design and development of a low cost shop floor control system for the modular furniture industry. An architecture in five hierarchical levels has been selected. An overview of the functions performed by line and workstation levels are described, likewise that information system part related with the control system. A detailed discussion about line level is presented and principally the incorporation of a Schedule Manager, based on an expert system. The proposed line level architecture and the software tools used in its implementation give a greater flexibility to the line control system.     

Negotiation-based collaborative planning in divergent two-tier supply chains

Advanced Planning Systems are based on the principles of hierarchical planning, which—at least at the top level—grounds on centralized planning. However, central coordination requires access to all relevant information and the power to impose planning results on all organizational units. In consequence it can be realized only for parts of an inter-organizational supply chain, and the question arises whether there exist alternate ways to achieve coordination. In this paper we describe a non-hierarchical, negotiation-based process, which can be used to synchronize plans between independent partners of a two-tier supply chain consisting of one supplier and several buyers. Assuming that all partners generate plans based upon mathematical programming—as in most Advanced Planning Systems at the master planning level—we show how modified versions of these models can be utilized to support the negotiation process by evaluating given purchasing orders or supplies and by generating counter-proposals. Resulting is an iterative, negotiation-like scheme, which establishes and subsequently improves a consistent overall plan based on a limited exchange of information between the supply chain partners.     

Collaborative agents for production planning and scheduling (CAPPS): a challenge to develop a new software system architecture for manufacturing management in Japan

Considering the frequent changes in market needs, real-time production management will produce huge additional value for manufacturers. As scheduling of shop floor operations is a local and partial decision in enterprises, the distributed local scheduling problems should be integrated at the enterprise level. Since decisions at the shop floor are very valuable, the next generation of production management will be performed as a decentralized system. This paper proposes architecture for scheduling-intensive production management. In the architecture, referred to as collaborative agents for production planning and scheduling, system integration is only achieved by communication among agents, i.e. a system is composed of loose connections between agents. As an implementation method, the paper introduces a standard specification for the communications among agents. The specification is recommended by PSLX, the Japan-based consortium for production planning and scheduling. The paper also shows some emerging business models on scheduling-intensive production management.     

Robust production planning and control for multi-stage systems with flexible final assembly lines

Production planning of final assembly systems is a challenging task, as the often fluctuating order volumes require flexible solutions. Besides, the calculated plans need to be robust against the process-level disturbances and stochastic nature of some parameters like manual processing times or machine availability. In the paper, a simulation-based optimisation method is proposed that utilises lower level shop floor data to calculate robust production plans for final assembly lines of a flexible, multi-stage production system. In order to minimise the idle times when executing the plans, the capacity control that specifies the proper operator–task assignments is also determined. The analysed multi-stage system is operated with a pull strategy, which means that the production at the final assembly lines generates demands for the preceding stages providing the assembled components. In order to guarantee the feasibility of the plans calculated for the final assembly lines, a decomposition approach is proposed to optimise the production plan of preceding stages. By this way, the robust production can be ensured resulting in reduced losses and overall production costs even though the system is exposed to changes and disturbances.