| 1. |
- Gernhardt, Benjamin, et al.
(författare)
-
Knowledge-Based Production Planning Within the Reference Planning Process Supporting Manufacturing Change Management
- 2016
-
Ingår i: Proceedings of the ASME 11TH International Manufacturing Science and Engineering Conference, 2016, VOL 2. - : AMER SOC MECHANICAL ENGINEERS.
-
Konferensbidrag (refereegranskat)abstract
- The manufacturing of a product takes place in several partial steps and these mostly in different locations to save tax or to use the best providers. Therefore, in the era of Internet of Things (IoT) and modem Intelligent Production Environments (IPE) are going to be inevitably based on a cloud-based repository and distributed architecture to make data and information accessible everywhere as well as development processes and knowledge available for worldwide cooperation. Semantic approaches for knowledge representation and management as well as knowledge sharing, access, and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient, and effective way. Thus, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required for e.g., Small and Medium Enterprises (SMEs). When such contributors work together on a product component production planning, they exchange component production and manufacturing change information between different planning subsystems which require, e.g., a standardized product-feature and production-machine feature representation. These data exchanges are mostly based on applying the already established Standard for the Exchange of Product model data (STEP) for the computer-interpretable representation and exchange of product manufacturing information. Furthermore, the planning process can be supported by so-called Function Block (FB) based knowledge representation models, serving as a high-level planning-process knowledge-resource template. Web-based and at the same time Cloud-based tool suites, which are based on process-oriented semantic knowledge-representation methodologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy the needs of representing such planning processes and their knowledge resources. In this way, WPIM can be used to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in Manufacturing Change Management (MCM) including Assembly-, Logistics and Layout Planning (ALLP). Therefore, also a collaborative planning and optimization for mass production in a machine readable and integrated representation is possible. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. To integrate all these functionalities, this paper introduces a new method, called Knowledge-based Production Planning (KPP) and outlines the advantages of integrating CAPP with Collaborative Manufacturing Change Management (CMCM). In this way, an enabling basis for achieving ALLP interoperability in Distributed Collaborative Manufacturing and Logistics will be demonstrated.
|
|
| 2. |
- Gernhardt, Benjamin, et al.
(författare)
-
Supporting production planning through semantic mediation of processing functionality
- 2016
-
Konferensbidrag (refereegranskat)abstract
- Semantic approaches for knowledge representation and management as well as knowledge sharing, access and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient and effective way. Therefore, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required in the CAPP-4-SMEs project. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP-4-SMEs request for a standardized production-feature representation. That can be achieved by applying so-called Function Block (FB) based knowledge representation models. Web-based and at the same time Cloud-based tool suites which are based on process-oriented semantic knowledge-representation methodologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy these needs. In this way, WPIM can be applied to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in a machine readable and integrated representation. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. Furthermore, semantic knowledge representation and querying will add value to the knowledge-based and computer-aided re-use of such machine-readable knowledge resources within CAPP activities. Finally, it will pave the way towards further automating planning, simulation and optimization in a semantic-web for CAPP.
|
|
| 3. |
|
|
| 4. |
- Givehchi, Mohammad, et al.
(författare)
-
Adaptive Distributed Process Planning and Executions for Multi-tasking Machining Centers with Special Functionalities
- 2015
-
Konferensbidrag (refereegranskat)abstract
- Today, the dynamic market requires manufacturing firms to possess a high degree of adaptability to deal with shop-floor uncertainties. Specifically targeting SMEs active in the metal cutting sector who normally deal with intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Cloud-DPP elaborates a two-layer distributed adaptive process planning based on function-block technology and cloud concept. One of the challenges of companies is to machine as many part features as possible in a single setup on a single machine. Nowadays, multi-tasking machines are widely used due to their various advantages such as reducing setup times and increasing part accuracy. However, they also possess programming challenges because of their complex configuration and multiple machining functions. This paper reports the latest state of design and implementation of Cloud-DPP methodology to support parts with a combination of milling and turning features, and process planning for multi-tasking machining centers with special functionalities to minimize the number of setups. The contributions of this work are: representation of machining states and part transfer functionality, support of multi-tasking machines in adaptive setup merging, development of special function blocks to handle sub-setups and transitions, and finally generation of function-block network for the merged setups. The developed prototype is validated through a case study.
|
|
| 5. |
- Givehchi, Mohammad, et al.
(författare)
-
An Evolutionary Operation Sequence Optimization Tool for Robotic Spot Welding Based on Collision-Free Path Planner in Virtual Manufacturing
- 2011
-
Ingår i: Proceedings of NAMRI/SME. - : Society of Manufacturing Engineers, North American Manufacturing Research Institution, NAMRI/SME. - 9780872638723 ; , s. 88-98
-
Konferensbidrag (refereegranskat)abstract
- Many problems in the lifecycle of Product and Production Development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described.
|
|
| 6. |
- Givehchi, Mohammad, et al.
(författare)
-
An Integrated Approach to Spot Welding Sequence Planning and Optimization
- 2010
-
Ingår i: Proceedings of the ASME 2010 International Manufacturing Science and Engineering Conference. - New York : ASME Press. - 9780791849477 - 9780791838877 ; , s. 543-551
-
Konferensbidrag (refereegranskat)abstract
- Almost in every discipline involved in Product and Production Development (PPD), optimization problems arrive. These real-world problems are too complex to be solved by analytical models and classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed more and more to create virtual representation models of the products under development and their related production facilities, processes, and systems in a virtual environment before any physical realization is conducted. Synergy of these two domains is of interest in this paper where a PPD problem requiring planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product was solved. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. The methodology is also required to be partially compliant to the concept of integrated Product-Process-Resource planning and optimization. An optimization tool is developed accordingly for operation sequence optimization integrated with a commercial VM environment.
|
|
| 7. |
- Givehchi, Mohammad, et al.
(författare)
-
An Integrated Approach to Spot Welding Sequence Planning and Optimization
- 2010
-
Konferensbidrag (refereegranskat)abstract
- Almost in every discipline involved in Product and Production Development (PPD), optimization problems arrive. These real-world problems are too complex to be solved by analytical models and classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed more and more to create virtual representation models of the products under development and their related production facilities, processes, and systems in a virtual environment before any physical realization is conducted. Synergy of these two domains is of interest in this paper where a PPD problem requiring planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product was solved. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. The methodology is also required to be partially compliant to the concept of integrated Product-Process-Resource planning and optimization. An optimization tool is developed accordingly for operation sequence optimization integrated with a commercial VM environment.
|
|
| 8. |
- Givehchi, Mohammad, et al.
(författare)
-
Cloud-DPP for distributed process planning of mill-turn machining operations
- 2017
-
Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier. - 0736-5845 .- 1879-2537. ; 47, s. 76-84
-
Tidskriftsartikel (refereegranskat)abstract
- Today, the dynamic market requires manufacturing firms to possess a high degree of adaptability to deal with shop-floor uncertainties. Specifically targeting SMEs active in the metal cutting sector who normally deal with intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Cloud-DPP elaborates a two-layer distributed adaptive process planning based on function-block technology and cloud concept. One of the challenges of companies is to machine as many part features as possible in a single setup on a single machine. Nowadays, multi-tasking machines are widely used due to their various advantages such as reducing setup times and increasing part accuracy. However, they also possess programming challenges because of their complex configuration and multiple machining functions. This paper reports the latest state of design and implementation of Cloud-DPP methodology to support parts with a combination of milling and turning features, and process planning for multi-tasking machining centers with special functionalities to minimize the number of setups. The contributions of this work are: representation of machining states and part transfer functionality, support of multi-tasking machines in adaptive setup merging, development of special function blocks to handle sub-setups and transitions, and finally generation of function block network for the merged setups. The developed prototype is validated through a case study.
|
|
| 9. |
- Givehchi, Mohammad, et al.
(författare)
-
Evolutionary optimization of robotic assembly operation sequencing with collision-free paths
- 2011
-
Ingår i: Journal of manufacturing systems. - : Elsevier. - 0278-6125 .- 1878-6642. ; 30:4, s. 196-203
-
Tidskriftsartikel (refereegranskat)abstract
- Many problems in the lifecycle of product and production development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and virtual manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
|
|
| 10. |
- Givehchi, Mohammad, et al.
(författare)
-
Function block-enabled operation planning and machine control in Cloud-DPP
- 2022
-
Ingår i: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; , s. 1-17
-
Tidskriftsartikel (refereegranskat)abstract
- Today, due to shop-floor uncertainties and widespread cross-enterprise collaborations, manufacturing systems of enterprises are increasingly demanded to be agile, adaptive, flexible and interoperable. Process planning systems are mission-critical constituent components of manufacturing systems in machining job shops of small and medium-sized enterprises in the machining and metal cutting sector. Cloud-based adaptive distributed process planning, which includes global supervisory planning in the cloud and local operation planning based on function block and cloud technologies, provides an effective approach for enhancing agility, adaptability, flexibility and interoperability of manufacturing systems.
|
|
