Challenges for the Automatic Generation of Simulation Models for Production Systems

This paper is intended as an introduction of the challenges that exist in the area of automatic simulation model generation in the production and logistics context. As a work-in-progress paper, it firstly analyzes and classifies previous work; it then introduces the most relevant challenges and lastly presents potential solutions currently being investigated by a PhD thesis

Development of a decision support app for short term production control to improve the adherence to delivery dates

In manufacturing, adherence to delivery dates is one of the main logistic goals. The production control department has to cope with short-term deviations from the planned route sheets. Because of unforeseen disruptions, e.g. machine breakdowns or shortage of material or personnel, in some situations, the promised delivery date to the customer is at stake. In practice, a fast and reasonable decision on how to deal with the delayed order is required. This decision process is often based on a qualitative analysis relying on the planner’s subjective assessment of a complex situation. To improve the quality of possible countermeasures this paper presents an application, which supports the decision process through a quantified analysis using real-time data from business application systems in combination with a simulation of the value stream. The developed app is part of the decision process and estimates the effect of selected countermeasures to accelerate a delayed order. Performance indicators illustrate the effect of the countermeasures on the specific order as well as the whole system. This approach empowers the planner to assess unforeseen situations and aims to improve the quality of the decision-making process. This paper describes the architecture of the application, its simulation ecosystem, the relevant data and the decision process to select the most effective countermeasures

Automatic generation of digital twin industrial system from a high level specification

A framework for the generation of industrial digital twins is presented in the paper. The framework supports industry automated systems preliminary design development, but also supports the following detailed designs implementation and final systems exploitation phases. The main problem is that requirements for first development phases are much more generic than those required for the later phases. The framework faces this problem by avoiding too detailed specifications for the digital twin generated software, but, at the same time, it takes advantage of the specific applications developed for each industrial implementation where that specificities are taken into account: the final control application and the management application. By properly linking both: the more generic digital twin and specific software applications specifically generated for the industry system, the framework may be ready to be used soon at the early development stages, but also may be used for detailed analyses at late booting and maintenance industry system phases. The system has been specialized in industrial transportation and warehouse systems. The paper presents an example of application for this kind of system

ANALYTICAL SOLUTION OF STEADY-STATE BEHAVIOR OF BERNOULLI PRODUCTION LINE WITH TWO FINITE BUFFERS

Production system engineering is strongly relied on mathematical models of systems under consideration and analytical solution of the problem has an important role in development and validation of more complex numerical tools. Analytical solution of steady-state behavior of serial Bernoulli production line with three machines and two buffers is considered in this paper based on Markov chain approach. Transition matrices in general case, including three machines with different probabilities of failure and arbitrary occupancy of two buffers, are formulated along with equations for performance measures. The developed theory is illustrated using four different serial Bernoulli lines and the obtained results are compared to those determined using semi-analytical approach via aggregation procedure. Finally, the existing discrepancies are analyzed and pointed out for five different levels of buffers occupancy. From general perspective, good agreement has been found for most of the results within the examined space of system states

The Hybrid Digital Twin: a practical way to connect simulation with operational production systems

Digital Twins are currently a topic of much discussion in academia. However, they have yet to be transferred to general industrial practice because there are still significant challenges concerning their implementation. This paper proposes the concept of the Hybrid Digital Twin to address these challenges. At first, it will elucidate the concept and introduce a real-world prototype of an operational production line. Afterwards, it will validate the prototypical implementation and demonstrate a detailed strategy to calibrate it. Then the paper presents potential strategies to use the Hybrid Digital Twin in a production environment. Finally, further developments and remaining issues are discussed

Automation potential of verification and validation techniques in discrete event simulation

Simulation is a proven method in industry and research to provide the basis for further decisions. Therefore, the credibility of its results is of major importance. Generally, simulation studies are guided by procedure models comprised of several phases with specific results. To assess the credibility, verification and validation (V&V) is used by applying V&V techniques to these phase results, which requires significant effort. One possibility to reduce this effort and support simulation users is to automate V&V. For this purpose, the notions of automation must be transferred to the domain of V&V in order to assess the automatability of V&V techniques. The effort for the application of V&V techniques can be reduced while maintaining or increasing the credibility of simulation

Simplifying the verification of simulation models through Petri net to FlexSim mapping

Simplifying the encoding of a simulation conceptual model representation reduces the number of errors that will be detected in the verification phase. In this paper, we present a mapping between Petri nets, a well-known formalism, and FlexSim, a well-known simulation tool. The proposal is illustrated through an example of how a model specified in a Petri net can be encoded easily, reducing the time needed to understand and verify the model. In the proposed methodology, the mapping must be defined at the initial stage of the encoding, starting from (in this case) a Petri net conceptual model, and ending at the encoding tool (FlexSim in this case). The main advantages of the proposed methodology are discussed.Peer ReviewedPostprint (author's final draft

Customized lean 3D simulation environment for intralogistics

PURPOSE: The aim of the article is to summarize the author's work, experiences, and publications in the form of a presentation of a coherent concept (requirements) for a simulation environment dedicated to intralogistics and based on Lean principles.DESIGN/METHODOLOGY/APPROACH: Methodology is based on taking into account the achievements of Lean and building it into the methodology of simulation modeling of intralogistics.FINDINGS: The findings include defined criteria for the evaluation of general-purpose simulation programs and dedicated program and their evaluation.PRACTICAL IMPLICATIONS: The presented approach and methodology is practically used in the LogABS simulation application introduced to didactics and offered on the market.ORIGINALITY/VALUE: As an original author contribution, this concept is, simulation modeling referred to as "one-to-one" in the description of processes carried out in the enterprise, changing the method of creating simulation models by defining mechanisms that automate the construction of models, adopting as the basis the analysis of the operations performed and not the states of the objects performing the operations, implementation of a cycle-based approach and cycle management, separation of the executive level from the decision level.peer-reviewe

Automatische Generierung adaptiver und lernfähiger Modelle zur Simulation von Produktionssystemen

In diesem Beitrag wird ein Ansatz zur automatischen Modelgenerierung und -adaption vorgestellt. Augenmerk liegt vor allem auf der Einsatzmöglichkeit im gesamten Produkt- bzw. Produktionslebenszyklus sowie bei der Integration in die betriebliche IT Infrastruktur, dazu wird auf standardisierten Datenaustausch mittels des Core Manufacturing Simulation Data (CMSD) Information Model gesetzt. Weitere Kernpunkte stellen die automatische Validierung und die Beschreibung bzw. Ermittlung von Steuerstrategien, z.B. Reihenfolgeregeln in Puffern, die Speicherung von manuell ergänzten Objekten/Verhalten und die Modellinitialisierung, dar. Die Beschreibung einer ersten prototypischen Implementierung einzelner Aspekte in Plant Simulation runden den Beitrag ab

Risk-Optimized Design of Production Systems by Use of GRAMOSA

Today production and logistic systems are getting more complex. This is a problem which the planning and design of such systems have to deal with. One main issue of production system development in series production is the planning of production processes and systems under uncertainty. New and existing production technologies are often not fully adoptable to new products. This is why some of the main characteristics, like, for example, cost, time, or quality, are not definable at the beginning. Only value ranges and probabilities can be estimated. However, the adaptation process is controllable, which means that the adaptation results are depending on the existing development budget and its resources. This paper presents an approach for the optimized allocation of development resources regarding the adaptation risks of production technologies and processes. The modeling concept GRAMOSA is used for integrated modeling and discrete event-based simulation of the aspired production system. To this end a domain-specific modeling language (DSML) is applied. The further risk-based analysis of the simulation results and the optimized allocation of the development budget are done by use of mathematical optimization