A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

An improvement of a cellular manufacturing system design using simulation analysis

Cell Formation (CF) problem involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the cellular manufacturing (CM) system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The objective of the proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares two strategies (1) permitting intercellular transfer and (2) exceptional machine duplication. The process is demonstrated with a numerical exampleCell Formation; Exceptional Elements; Simulation; Alternative costs; Improvement

A novel architecture for a reconfigurable micro machining cell

There is a growing demand for machine tools that are specifically designed for the manufacture of micro-scale components. Such machine tools are integrated into flexible micro-manufacturing systems. Design objectives for such tools include energy efficiency, small footprint and importantly flexibility, with the ability to easily reconfigure the manufacturing system in response to process requirements and product demands. Such systems find application in medical, photonics, automotive and electronic industries. In this paper, a new architecture for a reconfigurable micro manufacturing system is presented. The proposed architecture comprises a micro manufacturing cell with the key design feature being a hexagonal-base on which three tool heads can be attached to three of its sides. Each such machine-tool head, or processing module, is able to perform a different manufacturing process. These tool heads are interchangeable, enabling the cell to be configured to process a wide range of components with different materials, dimensions, tolerances and specification. Additional components of the cell include manipulation robots and an automated buffer unit. Such cells can be integrated into a manufacturing system via a modular conveyor belt to transfer parts from one cell to another and into assembly. A key consideration of the architecture is a control system that is also modular and reconfigurable; such that when new processing modules are introduced the control system is aware of the change and adjusts accordingly. Further to this coordination, issues between modules and machining cells are also considered. Other design considerations include work-piece holding and manipulation. This paper provides an overview of the architecture, the key design and implementation challenges as well as a high level operational performance assessment by means of a discrete event simulation model of the micro factory cell

Simulation Modeling in Manufacturing Cell Design

The interwoven phases of the manufacturing process in Computer Integrated Manufacturing (CIM) require a carefully designed facility. Simulation modeling can be combined with other techniques to provide a rigorous methodology for CIM system design. This paper describes CIM, simulation ana their relationship. A case study demonstrates the described methodology in the design of a flexible manufacturing cell

digital factory technologies for robotic automation and enhanced manufacturing cell design

The fourth industrial revolution is characterised by the increased use of digital tools, allowing for the virtual representation of a real production environment at different levels, from the entire production plant to a single machine or a specific process or operation. In this framework, Digital Factory technologies, based on the employment of digital modelling and simulation tools, can be used for short-term analysis and validation of production control strategies or for medium term production planning or production system design/redesign. In this research work, a Digital Factory methodology is proposed to support the enhancement of an existing manufacturing cell for the fabrication of aircraft engine turbine vanes via robotic automation of its deburring station. To configure and verify the correct layout of the upgraded manufacturing cell with the aim to increase its performance in terms of resource utilization and throughput time, 3D Motion Simulation and Discrete Event Simulation are jointly employed for the modeling and simulation of different cell settings for proper layout configuration, safe motion planning and resource utilization improvement. Validation of the simulation model is carried out by collecting actual data from the physical reconfigured manufacturing cell and comparing these data to the model forecast with the aim to adapt the digital model accordingly to closely represent the physical manufacturing system

Estimation of cellular manufacturing cost components using simulation and activity-based costing

It can be difficult estimating all of the cost components that are attributed to a machined part. This problem is more pronounced when a factory uses group technology manufacturing cells as opposed to a functional or process layout of a job shop. This paper describes how activity-based costing (ABC) concepts can be integrated into a discrete-event simulation model of a U-shaped manufacturing cell producing a part family with four members. The simulation model generates detailed Bills of Activity for each part type and includes specific information about the cost drivers and cost pools. The enhanced model output can be used for cost estimation and analysis, manufacturing cell design, part scheduling and other manufacturing decision processes that involve economic considerations. Although the scope of this effort is restricted to a small scale manufacturing cell, the costing concepts have general applicability to manufacturing operations at all levels

A Collision Detection Algorithm For Virtual Robot-Centered Flexible Manufacturing Cell

Collision detection is crucial in virtual manufacturing applications such as virtual prototyping, virtual assembly and virtual robot path planning. For accurate simulation of manufacturing systems and processes in virtual environment, physical interaction with the objects in the scene are triggered by collision detection. This thesis presents a collision detection algorithm for accurate simulation of a virtual flexible manufacturing cell. The technique utilizes the narrow phase approach in detecting collision detection of non-convex object by testing collision between basic primitive and polygon. This algorithm is implemented in a virtual flexible manufacturing cell for the loading and unloading process performed by the robot. The robot’s gripper is treated as non-convex object and the exact point of collision is represented with a virtual sphere and collision is tested between the virtual sphere and the polygon. To verify the collision detection algorithm, it is tested with different positions and heights of the storage system during simulation of the virtual flexible manufacturing cell. The results showed that the collision detection algorithm can be used to support the concept of hardware reconfigurablility of FMC which can be achieved by changing, removing, recombining or rearranging its manufacturing elements in order to meet new demands such as introduction of new product or change