Real time energy consumption analysis for manufacturing systems using integrative virtual and discrete event simulation

Manufacturing companies need greater capabilities to respond quicker to market dynamics and varying demands. Paradigms such as mass customization, global manufacturing operations and competition provide a platform to meet these needs. Therefore a continuous restructuring and re-engineering of the processes is seen in the manufacturing industries. This is extremely important in cases when automated machines are used in production. Automotive industry is an example of having intensive use of automated processes. During the reengineering of the processes it must be focused to control the factors which add cost during the processes. Energy is one of the important parameter which acts continuously over the process and increases the product price. Therefore, this paper proposes to validate the processes for energy optimization during the design stages well before, to physically build a machine. This could be done by using virtual environment and discrete event simulation integration. The pilot study of an ongoing research has been carried out to identify the level of energy consumption in a case study along with the identification of information to be used in the virtual tool prior to build the models. The adopted approach would propose to identify the processes to keep them off if consuming energy even in idle states. It could be identify through simulation that which one is the energy intensive process when they are idle, and then try it for the option, to keep it off when not working. Utilizing less energy in production helps society to have low cost products as well as to maintain the sustainable resources over a long period of time

Machine utilisation and breaksdown modelling for measuring productivity using virtual engineering simulation modelling

Results accuracy and reliability of discrete event simulation (DES) models to predict the production line productivities are based on the unexpected breakdowns taken place by machine faults or human errors. Process modeller practices DES modelling to incorporate these breakdowns and corresponding mainte-nances up-to the machine level. But actually breakdowns are potentially taken place at process level com-ponents inside the machine/stations. Domains like Virtual Engineering (VE) allow user to emulate the ac-tual machine build from components using the CAD data and thus define the components level processes model exist inside the machine station. Therefore author came with idea to integrate VE and DES model up-to component level processes to get an improved simulation modelling to analyse the machines breakdowns for validating pre-build and after-build phases of machine development. Initially in this arti-cle it was proposed to produce an algorithm required to integrate and model the component–level DES model driven from the available emulated data models

Development of a new learning methodology for discrete event simulation by reutilising previous software experience

New discrete event simulation software available to industry has significantly reduced the modelling efforts of complex manufacturing problems. These tools enable analysts to assess the viability of potential solutions that better conform to previously defined requirements. Thus, analysts must be conversant in new technologies applications to deliver top quality solutions to the enterprises analysed. Traditional approaches of learning a new technology tend to isolate previous knowledge the analyst possesses in similar application fields and concentrate on features and strengths of the particular application under study. A new approach is therefore needed to capitalise on previous experience an analyst might have, enabling reduction of learning a new technological application by minimising the learning curve effort spent learning the technology, and increasing focus on quantitative and qualitative analysis. [Continues.

Simulation support of lean layout considerations for new products: a case from large scale products

Planning a new production line for a product presents many opportunities to build best practice techniques into the new system. Set against the unknown quantities may be certain requirements for the production system to be lean, to have the flexibility to respond to market changes or make use of existing equipment of factory space. The unknown quantities can include: anticipated demand volumes, assembly and processing sequences, the specific production processes, lead-times of parts and components and even late changes to the product design after manufacturing/production decisions have been made. Simulations of a production system can be used to consider different scenarios and compare how well alternative approaches meet the defined requirements. [Continues.

Product to process lifecycle management in assembly automation systems

Presently, the automotive industry is facing enormous pressure due to global competition and ever changing legislative, economic and customer demands. Product and process development in the automotive manufacturing industry is a challenging task for many reasons. Current product life cycle management (PLM) systems tend to be product-focussed. Though, information about processes and resources are there but mostly linked to the product. Process is an important aspect, especially in assembly automation systems that link products to their manufacturing resources. This paper presents a process-centric approach to improve PLM systems in large-scale manufacturing companies, especially in the powertrain sector of the automotive industry. The idea is to integrate the information related to key engineering chains i.e. products, processes and resources based upon PLM philosophy and shift the trend of product-focussed lifecycle management to process-focussed lifecycle management, the outcome of which is the Product, Process and Resource Lifecycle Management not PLM only

Decomposition of automotive manufacturing machines through a mechanism taxonomy within a product lifecycle management framework

The automotive sector as with other manufacturing industries is under continual pressure from the consumer to deliver greater levels of product customisation at a higher quality and at reduced costs. Maintaining market position is therefore increasingly determined by a company's ability to innovate design changes quickly and produce greater numbers of product variants on leaner production lines with shorter times to market. In response manufacturers are attempting to accommodate product customisation and change through the use of reconfigurable production machines. Besides the need for flexibility, production facilities represent a significant investment for automotive manufacturers which is increasingly critical to commercial success; consequently the need to reduce costs through the reuse of assembly and manufacturing hardware on new product programs is becoming crucial. The aim of this research is to enable production machines to be more easily and cost effectively built and subsequently reconfigurable through the adoption of a component-based approach to their implementation utilising virtual manufacturing tools such as Product Lifecycle Management (PLM). It is suggested that through the decomposition of manufacturing machines into standardised mechanisms and their associated data structures a revised business model can be defined. The mechanisms are classified and deployed as part of a consistent integrated data structure that encompasses product, process and plant information. An objective is to properly integrate manufacturing data with more established Product Data Management (PDM) processes. The main areas of research reported in this article are, (1) development of a method for identifying and mapping data producers, consumers and flow, (2) development of standardised data structures for the management of manufacturing data within a PLM tool, (3) development of a taxonomy for the decomposition of manufacturing and assembly lines into a library of standard physical, logical and structural mechanisms and their associated interfaces. An automotive OEM case study is presented to illustrate the classification and management of production mechanisms focusing on an engine assembly line

A generalised approach to machine control

The intrinsic complexity and variability of typical real time control problems makes a generalised approach to producing control systems difficult to specify. Due to a lack of standardisation, current machine controllers are usually extremely difficult to configure, support and integrate together in a generalised manner. These problems have severely hindered the development and subsequent application of advanced factory automation. The exploitation of advanced computer technology, particularly modern software methods can now enable a consistent machine control structure to be maintained for diverse applications of widely differing complexity. This thesis addresses the need for a major change in the design of machine control systems and proposes the use of a reference architecture which offers a consistent approach to the control of real time industrial operations. A broad based look at existing control systems focuses on the functiona,lity they currently offer in the control of various categories of industrial operations. A study of current manufacturing automation highlights the functional similarities between the control requirements of different industrial processes both in terms of their control structure and hierarchical communication requirements for factory integration. Given this commonality it is proposed that all industrial controllers should logically be based upon a common hardware independent architecture. A design methodology has been devised, termed Universal Machine Control (UMC) which enables individual machine controllers to be created (with functionality closely matched to their specific applications) whilst still maintaining common structural and communications features. This methodology aims to simplify the process of defining, programming and controlling systems built up from user defined mechanical hardware. A modular design framework or reference architecture for machine control has been derived which allows control systems to be modelled in a generalised manner. A particular implementation of the control architecture conforming to this reference model and an associated definition environment have been created. The implementation is based on the selective use of modern computer methods and emerging standards for real-time control. A demonstration system has been produced targeted at the flexible assembly of printed circuit boards. The possible application areas for this control philosophy are however extremely diverse and it could have a significant impact on automation methods

Integration approach to virtual-driven discrete event simulation for manufacturing systems

Virtual engineering (VE) environment helps to verify process and resource design through visualisation. By using VE, the impacts of re-configurability and new-process additions in the machine stops can be viewed down to the component level. On the other hand, discrete event simulation (DES) typically forecasts the system behaviour over a period of time to predict future performance. During pre-build stages of machines, DES analysis comes with uncertainties, as most of the parameters in the model are based on the assumptions. Therefore, it was aimed to use the validated and verified data, for example ‘process time’ of a machine component available from the VE-emulated systems, in the DES model. Thus, a systematic algorithm was proposed to integrate the VE tool data, with the DES. This article presents the development of a package known as ‘virtual-driven discrete event simulation’ (VDSim), used to establish an integration between the VE and DES domains. The success of this integration depends upon the quality of information and the compatibility of data flow between these independent domains. VDSim integration will help productivity planners and schedulers to get the best possible options for resource selection at stages even when the resource is not physically present

Human system analysis for productivity indicators using virtual engineering simulation modelling

Continuous efforts are required to incorporate the human related variances when, to design human system. So far discrete event simulation techniques are used to document partially the human performance with respect to productivity using assumed and estimated data. This article proposes a new approach to enhance the estimated data used in discrete event simulation(DES) models with data available from virtual engineering(VE) models. Virtual models emulate the entire human and machine interacted processes, using the early available CAD data during production line design. Developing an integration between virtual engineering environment with DES model could help to validate and analyse the human system in modern manufacturing systems well before their physical appearance for productivities indicators. The on-going research particularly defines the algorithm used to model the human behaviour and model the probabilistic data available from the past activities to the discrete event simulation models through virtual engineering domain

Participants by institution and genotyping center in combined gold/silver standard association study.

<p>Abbreviations: MF, Marshfield Clinic Personalized Medicine Research Project; VU, Vanderbilt University BioVU; GH, Group Health/University of Washington Adult Changes in Thought and Alzheimer's Disease Patient Registry; MAYO, Mayo Clinic biobank; CIDR, Center for Inherited Disease Research.</p