Simulation for Product Driven Systems

Due to globalisation, companies have to become more and more agile in order to face demand fluctuations and growing customisation needs. Indeed, the mass production market moves to a mass customization one, which could be defined as the production of a wide variety of end products at a low unit cost. During last years, many efforts have been done in order to improve operating system reactivity (with the Flexible Manufacturing initiative for example), but the manufacturing decision process did not really change, and then doesn't enable to fully make the most of these new operating system skills. Facing these new trends, a lot of new research works are focusing on identification technologies, like Auto-ID, biometry or vision ones. Radio Frequency Identification technology (RFID) represents a quick and safe way to track products, opening the way of linking informational and physical flows, and providing an accurate, real time vision of the shop floor. These new technologies appear like a catalyst to change the fifty years old way of controlling production through traditional MRP² systems

The role of logistics in enhancing competitive advantage in global logistics organization

Abstract: Customer demands and increased competition create significant complexity for logistics organizations. Global logistics organizations are seeking the advantage of cost management, increased productivity and competitiveness. Companies that want to remain in business have to respond strategically and to fulfill the needs of customers. The objectives of the study are to determine the role of logistics in a global organization and to determine the relationship between applying continuous improvement and adoption of technology in enhancing competitive advantage in logistics. The study commences with a literature review to explore improvement methodologies and the adoption of information technology in logistics. The literature study discussed Value Stream Mapping as a lean tool and simulation as a tool to aid in decision making. The study narrowed to the warehouse operation of a global logistics organization...M.Phil. (Engineering Management

Exploring the potential of using radio frequency identification technology in retail supply chains - A Packaging Logistics perspective

In recent years RFID technology has attracted interest from the retail industry where it is being presented as a possible key to creating more efficient and effective retail supply chains. If RFID technology is to be implemented in packaging throughout retail supply chains, there is a need to develop an understanding of how and why the technology affects activities and processes within retail supply chains. Accordingly, the overall purpose of this licentiate thesis is to explore how the application of RFID technology to packaging could affect packaging logistics activities in retail supply chains. The packaging logistics activities discussed in this licentiate thesis are those related to ambient fast-moving consumer goods, from the product-filling point at the manufacturer’s, where the product is merged with the primary packaging, to the point of sale at retail outlets, where the products are sold to the end consumer. This thesis is based on multiple research strategies; a case study and a modelling and simulation study. The case study was conducted to describe and gain an in-depth understanding of and insight into existing packaging logistics activities in retail supply chains. A Dutch retail supply chain was chosen as a single-case study. The single-case study was both data-triangulated and investigator-triangulated with three Swedish case studies to further broaden the understanding of packaging logistics activities in retail supply chains. The case study resulted in a framework of packaging logistics activities in retail supply chains. The modelling and simulation study was conducted to describe what, how and why packaging logistics activities are affected when RFID technology is applied to packaging. A conceptual model and a simulation model were developed in the modelling and simulation study. The conceptual model describes and analyses “could-be” processes and activities in retail supply chains, whereas the simulation model primarily describes and anal

Regionalized implementation strategy of smart automation within assembly systems in China

Produzierende Unternehmen in aufstrebenden Nationen wie China, sind bestrebt, die Produktivität der Produktion durch eine Verbesserung der Lean Produktion mit disruptiven Technologien zu erreichen. Smart Automation ist dabei eine vielversprechende Lösung, allerdings können Unternehmen aufgrund von mangelnden Ressourcen oft nicht alle Smart Automation Technologien gleichzeitig implementieren. Ebenso beeinflusst eine Vielzahl an Einflussfaktoren, wie z.B. Standortfaktoren. Dementsprechend herausfordernd ist die Auswahl und Priorisierung von Smart Automation Technologien in Form von Einführungsstrategien für produzierende Unternehmen. Der Stand der Forschung untersucht nur unzureichend die Analyse der Interdependenzen zwischen Standortfaktoren, Smart Automation Technologien und Key Performance Indikatoren (KPIs). Darüber hinaus mangelt es an einer Methode zur Ableitung der Einführungsstrategie von Smart Automation Technologien unter Berücksichtigung dieser Interdependenzen. Entsprechend trägt diese Arbeit dazu bei, eine regionalisierte Einführungsstrategie von Smart Automation Technologien in Montagesystemen zu ermöglichen. Zunächst werden die Standortfaktoren, Smart Automation Technologien und KPIs identifiziert. In einem zweiten Schritt werden, mit Hilfe von qualitativen und quantitativen Analysen, die Interdependenzen bestimmt. Anschließend werden diese Interdependenzen auf ein Montagesystem mittels hybrider Modellierung und Simulation übertragen. Im vierten Schritt wird eine regionalisierte Einführungsstrategie durch eine Optimierung und eine Monte-Carlo-Simulation abgeleitet. Die Methodik wurde im Rahmen des deutsch-chinesischen Forschungsprojekts I4TP entwickelt, das vom Bundesministerium für Bildung und Forschung (BMBF) unterstützt wird. Die Validierung wurde erfolgreich mit einem produzierenden Unternehmen in Beijing durchgeführt. Die entwickelte Methodik stellt einen neuartigen Ansatz zur Entscheidungsunterstützung bei der Entwicklung einer regionalisierten Einführungsstrategie für Smart Automation Technologien in Montagesystemen dar. Dadurch sind produzierende Unter-nehmen in der Lage, individuelle Einführungsstrategien für disruptive Technologien auf Basis wissenschaftlicher und rationaler Analysen effektiv abzuleiten

Information Exchange in Global Production Networks: Increasing Transparency by Simulation, Statistical Experiments and Selection of Digitalization Activities

Today, companies of all industries are part of global production networks. They have a variety of performance relationships with suppliers and customers. Digitalization offers the potential to exchange more information between the partners of global production networks. This may improve operational performance. Especially within the three business processes order management, quality problem solving and engineering change management, a targeted increase in transparency promises a better handling of disruptions and an increase in robustness. This paper presents a simulation-based methodology for modeling production and business processes as well as information exchange in global production networks. Following the principles of Design of Experiment (DoE), screening test plans first carve out the impact of disruptions and information exchange on the performance of the production network. This is followed by the determination of the disruption-robust information exchange using Taguchi-experiments. Starting from the actual state of information exchange, digitalization activities to increase transparency are finally determined. The activities consist of the implementation of digitalization technologies and the stronger linkage of information systems. The paper ends with an application of the methodology to a global production network for plastic-metal components in the automotive supplier industry

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets

Ageneric predictive information system for resource planning and optimisation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe purpose of this research work is to demonstrate the feasibility of creating a quick response decision platform for middle management in industry. It utilises the strengths of current, but more importantly creates a leap forward in the theory and practice of Supervisory and Data Acquisition (SCADA) systems and Discrete Event Simulation and Modelling (DESM). The proposed research platform uses real-time data and creates an automatic platform for real-time and predictive system analysis, giving current and ahead of time information on the performance of the system in an efficient manner. Data acquisition as the backend connection of data integration system to the shop floor faces both hardware and software challenges for coping with large scale real-time data collection. Limited scope of SCADA systems does not make them suitable candidates for this. Cost effectiveness, complexity, and efficiency-orientation of proprietary solutions leave space for more challenge. A Flexible Data Input Layer Architecture (FDILA) is proposed to address generic data integration platform so a multitude of data sources can be connected to the data processing unit. The efficiency of the proposed integration architecture lies in decentralising and distributing services between different layers. A novel Sensitivity Analysis (SA) method called EvenTracker is proposed as an effective tool to measure the importance and priority of inputs to the system. The EvenTracker method is introduced to deal with the complexity systems in real-time. The approach takes advantage of event-based definition of data involved in process flow. The underpinning logic behind EvenTracker SA method is capturing the cause-effect relationships between triggers (input variables) and events (output variables) at a specified period of time determined by an expert. The approach does not require estimating data distribution of any kind. Neither the performance model requires execution beyond the real-time. The proposed EvenTracker sensitivity analysis method has the lowest computational complexity compared with other popular sensitivity analysis methods. For proof of concept, a three tier data integration system was designed and developed by using National Instruments’ LabVIEW programming language, Rockwell Automation’s Arena simulation and modelling software, and OPC data communication software. A laboratory-based conveyor system with 29 sensors was installed to simulate a typical shop floor production line. In addition, EvenTracker SA method has been implemented on the data extracted from 28 sensors of one manufacturing line in a real factory. The experiment has resulted 14% of the input variables to be unimportant for evaluation of model outputs. The method proved a time efficiency gain of 52% on the analysis of filtered system when unimportant input variables were not sampled anymore. The EvenTracker SA method compared to Entropy-based SA technique, as the only other method that can be used for real-time purposes, is quicker, more accurate and less computationally burdensome. Additionally, theoretic estimation of computational complexity of SA methods based on both structural complexity and energy-time analysis resulted in favour of the efficiency of the proposed EvenTracker SA method. Both laboratory and factory-based experiments demonstrated flexibility and efficiency of the proposed solution.The Engineering and Physical Sciences Research Council