A STRUCTURED APPROACH TO SIMULATE MANUFACTURING SYSTEMS IN VIRTUAL ENVIRONMENT

CAPUTO, Francesco; DI GIRONIMO, Giuseppe; MARZANO, Adelaide

University of Naples Federico II Dipartimento di Progettazione e Gestione Industriale

e-mail:{francesco.caputo, giuseppe.digironimo, a.marzano}@unina.it

ABSTRACT

Nowadays, the realization of the Virtual Factory (VF) is the strategic goal of many manufacturing enterprises for the coming years. The industrial scenario is characterized by the dynamics of innovations increment and the product life cycle became shorter. Furthermore products and the corresponding manufacturing processes get more and more complex. Therefore, companies need new methods for the planning of manufacturing systems. To date, the efforts have focused on the creation of an integrated environment to design and manage the manufacturing process of a new product. The future goal is to integrate Virtual Reality (VR) tools into the Product Lifecycle Management of the manufacturing industries. In order to realize this goal the authors have conducted a study to perform VF simulation steps for a supplier of Industrial Automation Systems and have provided a structured approach focusing on interaction between simulation software and VR hardware tools in order to simulate both robotic and manual work cells. The first results of the study in progress have been carried out in the VR Laboratory of the Competence Regional Centre for the qualification of the Transportation Systems that has been founded by Campania Region.

Key words: Virtual Manufacturing, Virtual Reality tools, Ergonomic analyses, Robotic simulations.

1. Introduction

Simulation is a powerful tool to analyze manufacturing systems for purposes of design and on-going operation. In recent years, simulation modeling and analysis have been enhanced significantly by increasingly powerful computational platforms. This has enabled development of high-fidelity models of manufacturing systems, at least from a computational perspective. Such high-fidelity modeling has important benefits in prototyping system performance; however, it must be supported by an underlying modeling discipline, or structured approach to modeling factory operations. In this paper, the authors describe results of Virtual Reality (VR) integration in Product Development, based on a reference model of manufacturing systems.

Like many emerging simulation technologies, VR has overcome the excitement and hyperbole of its early promise and matured into useful product development tool in a variety of manufacturing industries.

Before beginning any analysis about the variegated and complex world of Virtual Manufacturing (VM), it is necessary to fix some “stones” about what VM is. The term Virtual Manufacturing is now widespread in literature, but several (and sometimes different) definitions are related to it. A lot of VM applications can be find in different fields such as casting, forging, sheet metalworking and robotics, but the general idea comprises a concept: Virtual Manufacturing is “manufacturing in the computer”[1]. The comparison between VM and VR is discussed in [2], [3]: it’s stated that “VR represents a tool which offers visualization capabilities for VM”. A more comprehensive definition has been proposed by the Institute for Systems Research, University of Maryland [4] : VM is defined as “an integrated, synthetic manufacturing environment exercised to enhance all levels of decision and control”.

The goal of the paper is to answer the following questions:

- What are the steps to realize a complete and useful virtual manufacturing simulation?

- How is it possible to realize a “fusion” between the virtual and the physical world?

- What are the critical factors that help designers in realizing virtual simulations?

This paper gives the answers in the following steps:

- Description of actions is detailed, starting from the “naked idea” till to complete virtual simulation.

- The fusion is realized by VR tools, integrated in Product Development Process.

- Critical keywords are “modularity”, in the meaning of different stand-alone dedicated tools that can be integrated, and “data exchange”, because it’s necessary to allow different designers and customers to manipulate information in the same format, that means less probability of misunderstandings and failures.

The work is divided into four parts. The first part is a survey about “state of the art” of Virtual Simulation in manufacturing environment. In the following section, industrial requirements and needs from Virtual Simulation software are pointed out. Then, commercial software benchmarking is performed. In the last part of the work, an approach for ergonomic evaluation of manual work cells is presented, with focus on interaction between simulation software and Virtual Reality tools.

2. Related work

With roots primarily in university research laboratories, VR enjoyed a flurry of commercialization in the early - to mid- 1990’s resulting in a numerous hardware and software technology providers. However, the relatively high cost, lack of compelling applications, and lack of integration with existing processes, conspired to dampen the initial excitement of many manufactures for VR. As a result, the past ten years has seen a dramatic consolidation in the commercial VR technology industry. In fact in manufacturing environment many software packages have been developed for virtual applications [5]. These packages provide authoring applications that can be used to develop and create virtual manufacturing environment to address process planning, cost estimation, factory layout, ergonomics, robotics, machining, inspection, factory simulation, and production management.

In [6] VR applications in manufacturing field have been classified into three groups; operation management, manufacturing processes and design. In design area the benefits of the applying VR in manufacturing applications are to improve visualization of the product by allowing the user to co-exist in the same environment with the product model [7], to allow the users to interact and change the model during runtime [8]. In operations management, like training and planning the benefits are: to support technological as well as economical modeling of diverse production planning scenarios [9]; to duplicate an entire manufacturing process to a virtual environment giv ing the trainers their own factory to learn in; to provide a user with an environment to explore the outcomes of their decisions without risk themselves or equipment. GM Daewoo [10] developed an off-line programming (OLP) system, which generated the robot-teaching program by simulation. This OLP system allows GM Daewoo to model the end-to-end production line and to validate the process in a virtual environment drastically reducing development time. Major benefits such as cost reduction and shorter time-to-market have been recorded thanks to these packages.

In manufacturing processes the most important applications realized are in assembly area in order to reduce design cycle time, redesign efforts, to predicted the quality of an assembly, product cycle and cost, to provide an environment for studying the inspection methodologies and collision detection. For over ten years the Institute of Industrial Technology and Automation of National Research Council (ITIA-CNR) has been active in the Research & Development (R&D) of new manufacturing systems and innovative production paradigms. Some of its research activities include Parallel Kinematics Machines (PKM), product and process life cycle innovation, studies and projects on the extended enterprise, process simulation in machining and assembly and development of the VR environment for immersive interaction. During the last ten years, ITIA has tested and used several software programs for process and kinematics simulations [11].

3. Industrial Requirements

Final target of many Original Equipment Manufacturers (OEMs) is Virtual Factory: it can be reached with the integration of different software tools, each dedicated to simulate three main production environments: manual work cells, robotized work cells, Numeric Control (NC) Machining. A fourth tool is needed to import models from the previous three environments, and build up the whole production plant simulation. In order to realize this goal, there is a couple of aspects to take into account: modularity of software tools and data compatibility. In fact, to opportunely divide activities into working groups, and after assembly simulation blocks into a ‘global’ simulation, each tool (ergonomics, robotic, etc.) has to be ‘stand-alone’, and data-exchange between tools must be easy, fast and safe.

In order to realize a virtual simulation, in a manufacturing environment, the following actions have to be performed (Figure 1):

PDM SYSTEM

CAD MODELS SIMULATION DATA OTHER DATA

ERGONOMICSIMULATION

WORKCELL SIMULATION

ROBOTIC SIMULATION

OUTPUT ANALYSIS

PLANT SIMULATION

MANUFACTURING SIMULATION

PRESENTATION TO COSTUMERBUSINESS MANAGMENT

Figure 1: Sequence of actions to perform a manufacturing simulation

1. Data collection (layout, 3D models, pictures, sequence of operations, assigned cycle time, productivity, availability, etc.). Prediction data from Reliability & Maintenance (R&M) office are continuously supported and brought to state-of-the-art by monitoring and verifying on field.

2a. Work cells Simulation using dedicated software tools. Modularity of software is crucial in this phase, to allow designers to work parallel and decrease work-time. Ergonomic evaluations for manual work cells and robotic simulations for automatized work cells are included.

2b. Simulation of line/plant flow of production. Until phase 2a. is not completed, each machine or manual station can be represented as a “black box” with assigned cycle time, failure rate, availability etc.

3. Integration of each machine/station into plant discrete event simulation tool. Now simulation is complete, and output data can be analyzed.

4. Output analysis: it must be verified that each assigned parameter, such as technical efficiency, availability or throughput, fit with customer’s requirements (better, with contract terms). If data are satisfactory, the whole simulation work can be presented to customer. If not, data flow back to engineers (red line in the diagram of figure 1) that can change parameters as well to correct the problem.

5. Presentation of the whole work to customer.

4. Virtual Factory simulation steps

The simulation model is realized using, basically, four kind of software. A CAD package is used for modeling the geometry of components. Three simulation tools, classified for work area, such as discrete events simulation for plant simulation, robotics and ergonomics, are used to simulate each workplace and the overall flow of the line. Table 1 shows the most important VF software adopted in manufacturing field classified for work area.

Table 1: Virtual Factory software

TOOL SOFTWARE HOUSE AREA

ARENA ROCKWELL

AUTOMOD BROOKS AUT.

DELMIA - QUEST DASSAULT SYSTEMES

FACTORY CAD UGS

DISCRETE EVENT PLANT SIMULATION

DELMIA - IGRIP DASSAULT SYSTEMES

eM-WORKPLACE (ROBCAD)

UGS ROBOTICS

DELMIA - ERGO/HUMAN DASSAULT SYSTEMES

JACK UGS

ERGONOMIC EVALUATIONS

4.1. Object modeling

The CAD system used for modeling objects is both a two and a three-dimensional (2D-3D) design and drafting platform that automates design tasks. The components and subassemblies of the product and tools, input and output bins, subassemblies and fixtures are modelled manually using the CAD tools.

The models of the components and the assemblies are exported into the simulation software using appropriate file export features.

4.2. Robotic simulations

In modern production plants, it’s easy to see a massive use of robots, principally anthropomorphous. They can get fast, accurate and efficient a wide range of operation such as various kinds of assembly, “pick and place” operations, fastening, as well as welding. In general, Computer Aided Robotics Systems (CAR-System) are used to design robot cells and to create the offline programs necessary to reduce start-up time and to achieve a considerable degree of planning reliability. The use of simulation for the planning and designing of robot cells and plants has increased substantially in recent years. Generally, commercial CAR-Systems can be divided into main groups: high-end and low-cost.

The best known high-end CAR-Systems used in manufacturing environment are eM-Workplace (formerly ROBCAD) by UGS and Delmia - IGRIP by Dassault Systemes. These systems have been developed to meet the specific requirements of the production industry and can accomplish an amazing array of tasks. They integrate functionality for special tasks such as spot welding, laser application dispensing, and painting. With these tools, it is possible to simulate multiple robots from different manufactures at the same time.

In the Table 2 is showed a comparison between eM-Workplace and IGRIP focusing the attention on features such as CAD supported/data exchange capability, integration with VR tools, open architecture.

Table 2: eM-Workplace vs. IGRIP.

SOFTWARE MAIN

PROPERTIES DELMIA - IGRIP BY DASSAULT SYSTEMES

EM-WORKPLACE (ROBCAD) BY UGS

CAD SUPPORTED/DATA

EXCHANGE CAPABILITY

DIRECT CAD INTERFACE: Catia V5, Unigraphics NX, Pro/Engineer, Autocad.

NEUTRAL FORMATS: IGES, DXF, STEP, STL.

DIRECT CAD INTERFACE : Catia V5, Unigraphics NX, Pro/Engineer.

NEUTRAL FORMATS: IGES, DXF, STL, STEP.

ROBFACE: a Tecnomatix neutral data exchange format enables the implementation of any kind of dedicated MCAD interface.

INTEGRATION WITH VIRTUAL REALITY TOOLS

Cyber-Glove, Ascension Flock Of Birds, Stereo Display Interface.

VD2 (VRCOM), INVISION (INTRO)

OPEN ARCHITECTURE

Allows users to program custom function with unparalleled ease by creating menu functions, custom device kinematics and motion planning algorithms.

The tool EM-ROSE API offers an open system environment for developing customized features and applications. It provides high-level access to EM-WORKPLACE proprietary core technologies and algorithms, including geometry, kinematics, motion planning and graphics.

4.3. Ergonomic simulations

In the 80’s and early ’90, manufacturing industry exponentially increased the automation level into factories. OEMs were dreaming about a completely robotized production system. Through the years, indeed, this ideology crashed with a lot of obstacles and contraindications, such as low availability and efficiency, high cost of machines and maintenance. But the principal reason, in the recent past, that brought back to a massive use of manual operations in factories, was the irruption into the world scenario of new markets (Far East, South America), with dramatic manpower’s cost reduction. That’s why ergonomic simulation is getting more and more critical in a Virtual Factory approach.

Two of main commercial software tools for ergonomic simulation are benchmarked, Delmia - ERGO (by Dassault Systemes) and JACK (by UGS) [12]. It must be cleared that ERGO is most properly an add-on of IGRIP; in particular it can be used to model assembly and materials handling operations between workstations.

Those tools are basically used to design safe working environments that accommodate a wide range of workers and for ergonomic assessment and task analysis. It is used to address the human interface issue that impacts the ability of a wide range of humans to assemble the prototype product and the process times needed for each task. Libraries of whole body, head, arms and hand postures are used. The software also provides “point and click” routines to generate walking, climbing, lifting and carrying sequences.

In ERGO, to model a workstation operation, the worktable, parts and bins and human operator are imported as “devices” and placed at appropriate locations in the workstation. Using the ergonomics option, the human device was “taught” to perform the assembly process by creating a series of positions of the human hands while holding and assembling the product [13].

Figure 2 shows examples of workstations and operators modelled in IGRIP/ERGO, while Figure 3 shows a work cell in a train’s assembly cycle realized by JACK.

Figure 2: Work cell simulation with IGRIP (on the left) and ERGO (on the right)

Figure 3: Simulation of a Manufacturing Process with JACK: working on a work cell in a train’s

assembly cycle .

In order to research which of the software tools adopted by a manufacturing industry can be integrated with virtual reality tools, has been conduct a comparison between ERGO and JACK [12], as showed in table 3.

Table 3: ERGO vs. Jack.

SOFTWARE

MAIN PROPERTIES DELMIA – ERGO

BY DASSAULT SYSTEMES

JACK BY UGS

ERGONOMIC EVALUATION

TOOLS

HUMAN BUILDER

HUMAN TASK SIMULATION

HUMAN ACTIVITY ANALYSIS

HUMAN POSTURE ANALYSIS

HUMAN MEASUREMENTS EDITOR

TASK ANALYSIS TOOLKIT :

Niosh Lifting Analysis; Rapid Upper Limb Assessment (Rula); Metabolic Energy Expenditure; Manual Material Handling Limits; Static Strength Prediction; Ovako Working Posture Analysis System (Owas); Fatigue And Recovery Analysis; Low Back Compression Analysis; Predetermined Time Analysis.

INTEGRATION WITH VIRTUAL REALITY TOOLS

3D INPUT DEVICE:

Cyberglove Spaceball Joystick

TRACKING SYSTEMS:

Fakespace Polhemus

3D INPUT DEVICE:

Cyberglove

TRACKING SYSTEMS:

Vicon Flock Of Birds

4.4. Plant simulations

According to steps detailed in section 3, also discrete-event plant simulation tools are benchmarked. ARENA is 2D plant workflow simulation. It’s more oriented to output data (reliability, productivity, efficiency, bottlenecks detection) than to graphic representation of the plant itself. AUTOMOD, on the opposite, allow a three-dimensional visualization [14]. Delmia - QUEST is an object-based, discrete event simulation tool. It is used to model, experiment with, and analyze facility layout and process flow. It provides visualization and data import/export capabilities.

The process of incorporating workstation sub-models into the discrete-event simulation model is basically simple. Initially, the workstation operation is played and recorded in the graphical modeling application. It is then exported as a QUESTCELL file. The display option provides in the discrete event-simulation tool; each station is displayed as the imported workstation sub-model. Similarly, the scripts associated with a human carrying a bin of components or subassemblies between stations are determined and imported. Figure 3 shows what the QUEST simulation model looks like after importing and integrating the workstation models that were developed in IGRIP [15].

Figure 4: Plant simulation with DELMIA - QUEST.

Concurrent discrete event tool is FactoryCAD by UGS. This software allows to work with “smart objects” that represent virtually all the resources used in a Factory, from floor and overhead conveyors, mezzanines and cranes to material handling containers and operators. With these objects, it’s possible to “snap” together a layout model without wasting time drawing the equipment. Starting from a 2D layout drown using Autocad GUI, FactoryCAD allows to develop the project in 3D using a complete 3D object library.

5. Use of Virtual Reality for manufacturing systems simulation

Taking into account what has been stated in Section 3, the authors have investigated the possibility to integrate VR tools in the overall flow of a vehicle production simulation (Figure 5).

ROBOTIC SIMULATION

VR SYSTEM

WORK CELL SIMULATION

ERGONOMIC EVALUATION

PLANT SIMULATION

PDM SYSTEM

CAD MODELS SIMULATION DATA OTHER DATA

PRESENTATION TO COSTUMER

Figure 5: VR integration in overall flow of simulation

First of all, in order to achieve this integration it is necessary the develop a procedure for the Virtual Prototyping that foresees, in particular, an optimization of the management of data exchange protocols between 3D parametric CAD systems and visualization environments using meshed models.

One of the most pressing issue facing industry is data integration. The CAD systems used to realize product models are generally not suited to producing a representation conducive to large scale and a frame rate guaranteed visualization required by VR applications. Although addressed to some degree by commercial providers of visualization software (such as UGS PLM Solution and Dassault Systemes) there is no general non-proprietary way to convert a CAD assembly into a representation suitable for VR (Figure 6).

PDM SYSTEM

CAD DESIGN PREPARATION TOOL

VR SYSTEMEVALUATION, SIMULATION, VERIFICATION

Figure 6: Data flow between CAD and VR system.

The second step is the arrangement of a virtual environment in which it is possible to simulate assembling operations of products belonging to the manufacturing field, that means build up the “scene” where the operations take place, then it is possible to realize the work cells simulation by integrating VR tools. As the Figure 5 shows, there are three fields in which the VR could be integrated: ergonomics, robotics and factory layout simulation.

The following figures show the case study proposed by a global supplier of industrial automation systems for the automotive manufacturing in which the authors are developing, in the “VRTest” Laboratory of the Competence Regional Centre for the qualification of Transportation Systems that has been founded by Campania Region [16], an ergonomic optimization approach as described below.

Figure 7: Body Welding Work cells.

The approach that the authors propose is structured in three steps:

A. development of a methodology for ergonomic optimization based on the use of digital human models and virtual reality techniques in order to simulate in a virtual environment the human performances during the execution of assembly operations.

B. Ergonomic evaluation of manual work cells trough a direct manual interaction approach in VR.

In order to reach this aim it’s necessary to integrate in a single visualization and development environment, tracking system (ART DTrack), manipulation systems (5DT Data Glove and CyberGlove), 3D navigation devices (SpaceBall, Flystick and Joystick) and stereoscopic visualization systems (Powerwall and Helmet such as Head Mounted Display). In this environment the user, who wears HMD, glove and tracking sensors, have the opportunity to execute, directly on the virtual model of the work cell, “subjective” ergonomic analyses simulating assembly, welding (Figure 8) and handling operations. The evident advantage of the direct manual interaction approach consists in the immediate correspondence between the desired analysis and the relative action carried out. This correspondence makes the performed analysis natural, intuitive, and, consequently , quick. Regarding the objectivity of the analysis results, the virtual manikin approach gives more flexibility because it easily allows several human models, corresponding to different percentiles, to repeat the same actions.

Instead, the direct manual interaction approach presents, from this point of view, a lower correspondence to reality: in this case, in order to obtain more objective results, it is necessary to carry out a statistical analysis, through subjective tests on a representative sample of human population. However, the approach with virtual manikins in the analyses of assembly or maintenance operations shows the disadvantage of moving the various degrees of freedom of the digital human model (135 for Jack of the EAI-UGS, 86 for Delmia - Ergo) by inadequate input devices like mouse and keyboard.

In Figure 8 an accessibility evaluation of a welding pincers is simulated by direct manual interaction through a virtual hand. By this method the evaluation is subjective as aforementioned, but it is possible to evaluate the layout configuration of the tools (the welding pincers) in order to improve the tasks of the operator.

Figure 8: Grasping of a Welding Pincers in Virtual Environment.

C. Ergonomic analysis of manual work cells trough integration between virtual human model and manual direct interaction.

In order to overcome such disadvantages mentioned above (e.g., virtual manikins and direct manual interaction) the authors propose to investigate the possibility of moving virtual manikins tracking directly the motions of a human on which they have preventively disposed some sensors in opportune positions.

In many manufacturing industry the work cells are both manual and robotic, so in these cases the advantage of the integration of VR tools is to evaluate in real size:

• the representation of active areas and safety margins;

• consideration of workspaces;

• adherence of minimum and maximum distances between machines;

and the interaction of these factors with the human being.

The same evaluations can be valid for the plant simulation in VR; it is useful displaying the VF layout to examine space requirements for workers and products in the factory. Current traditional factory layout applications are limited to display scaled versions of the factory on a computer monitor. With VR, the factory products and machines can be placed in real size in the VF. Workers can enter the VF, manipulate virtual product, and evaluate the layout of work cells.

6. Conclusions

This work aims basically to offer an overall view about the potentialities, not yet adequately expressed, which simulation technologies based on VR can provide to the improvement of production systems. The resources employed in VR application to design, either installation, management or upgrading costs, are remarkable. For this reason, to date, the application actually developed are relative to those industrial fields, such as automotive and aeronautics, which could sustain the costs.

Acknowledgements

The authors, that have developed the present work with an equal contribute, deeply thank prof. Antonio Lanzotti, Dr. Ing. Stanislao Patalano, Ing. Stefano Papa, Ing. Francesco Apperti and Ing. Fulvio Rusinà for their helpful discussions and suggestions about future works. The present work has been developed with the contribute of POR Campania 2000-2006 – MIS 3.16, performing the activities of the Competence Cente r for the Qualification of Transportation Systems founded by Campania Region.

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