A Classification of Different Levels of Flexibility in an Automated Manufacturing System and Needed Competence

Nilsson, Anders; Danielsson, Fredrik; Bennulf, Mattias; Svensson, Bo

doi:10.1007/978-3-030-90700-6_2

Cited by 7 publications

(4 citation statements)

References 17 publications

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“…This approach has been proposed by researchers for a long time, but few proposals have been implemented in the industry. One reason is connected to the fact that flexible systems are too complex to handle, few researchers consider that more flexibility and adaptivity appear to demand a higher degree of competence to handle [6]. This article aims to break that trend by redirecting the complexity from focusing on the machines to focusing on the parts and their manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

A Generic Structure for the Integration of Customized Industrial Gantry Robots into Agents of Plug & Produce Automated Manufacturing System

Nilsson,

Danielsson

2024

Advances in Transdisciplinary Engineering

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The demand for customized products in a saturated market of trendy customers forces the manufacturing industries to transform their manufacturing from a high volume of uniformed products to low volumes and a high mix of products. High mix and low volume manufacturing is most often manually performed since existing automation solutions are only profitable for mass manufacturing, due to explicitly designed control software where the product data is implemented as low-level control code. Highly flexible automated manufacturing systems such as Plug & Produce are requested, but challenges still exist before industrial implementation. This article proposes a digitally configurable system where data for new or modified products data is configured from the perspective of the product and its manufacturing processes instead of the manufacturing resources. In a Plug & Produce system, process modules with manufacturing resources are easy to replace for new or modified products and possibly to duplicate if higher capacity is needed. Configurable multi-agent systems are proposed by several researchers as a control system for Plug & Produce. An agent is a piece of autonomous computer code that negotiates with other agents and concurrently solves tasks, distributed on parts and resources. A part is a part of a product and part agents handle manufacturing goals for the parts. Resource agents know their capability and start operating as soon as they are plugged in. Resource agents follow pluggable process modules containing manufacturing resources and act as drivers for the modules. Gantry robots have by design a naturally orthogonal coordinate system and most often lack the functionality to handle work and tool coordinate objects as standard industrial robots do. Work objects refer to a base coordinate system and tool objects contain a reference to the tool center point. These references are in this article integrated into resource agents together. A place coordinate agent has the global perspective of the Plug & Produce cell and provides the process modules with reference coordinates of the place they are plugged into. Coordinates are recalculated from a product perspective into a resource perspective by coordinate transformations built into the skills of resource agents. This structure enables the possibility for process planners in the manufacturing company to make changes on a daily basis. A test with a gantry robot Plug & Produce demonstrator was performed and presented in this article to verify the generic structure of the gantry robot control system into agents.

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Section: Introductionmentioning

confidence: 99%

A Generic Structure for the Integration of Customized Industrial Gantry Robots into Agents of Plug & Produce Automated Manufacturing System

Nilsson,

Danielsson

2024

Advances in Transdisciplinary Engineering

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“…Hence, reconfigurable and by design flexible control systems are questioned [1]. However, the situation in the industry is that a high degree of flexibility in automation systems requires a high degree of competence to handle [2]. This article aims to change this relationship by expanding an existing Plug & Produce concept, controlled by the Configurable Multi-Agent system (C-MAS) [3].…”

Section: Introductionmentioning

confidence: 99%

From CAD to Plug & Produce - A generic structure for the integration of standard industrial robots into agents

Nilsson

Danielsson²,

Svensson³

2023

Preprint

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Industries of low batches or one-off manufacturing aim for automation that is competitive enough to adapt to new or modified products daily through in-house knowledge. A knowledge that focuses on manufacturing processes, not on machine function programming. To solve this a complete set of actions that utilize seamless data transfer from product design to a Plug & Produce automation concept is proposed together with a generic structure for the integration of standard industrial robots into agents. This structure enables agents to handle their local reference coordinate systems and locations relative to a global perspective. Seamless utilization of data from product designs to Plug & Produce will simplify and shorten the time of digital development through concurrently usable text-based and graphical configuration tools of a configurable multi-agent system. Needed data extracts directly from the product design as requirements of operational goals. Extraction of data from the product design, sequence of goals, and process plans, which are recipes of how to solve goals, can by this concept be configured by in-house knowledge that has the process knowledge but not necessarily programming competence.

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“…Manufacturing facilities designed for dedicated production in various industries encounter problems when transitioning to accommodate customization. It is difficult to accommodate customized products with low-volume production based on individual customer needs [2]. These traditional dedicated manufacturing systems are time-consuming to alternate, often taking months to reconfigure the manufacturing to accommodate the customized products [3].…”

Section: Introductionmentioning

confidence: 99%

“…These traditional dedicated manufacturing systems are time-consuming to alternate, often taking months to reconfigure the manufacturing to accommodate the customized products [3]. Again, when the product specification is changed, then industries must go through the entire reconfiguration again, meaning major investment costs are necessary for reconfiguration, which may be hard to motivate, whereas the flexibility of concepts like Plug & Produce (P & P) will reduce the cost and time of a redesign or reconfiguration, thereby allowing for quicker response to the customers and providing customized products with increased performance [2]. Flexibility can be brought into the production system in several ways, i.e., product flexibility, manufacturing flexibility, hardware flexibility, and enterprise flexibility.…”

Section: Introductionmentioning

confidence: 99%

Sampling-Based Path Planning Algorithm for a Plug & Produce Environment

Ramasamy,

Eriksson,

Danielsson

et al. 2023

Applied Sciences

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The purpose of this article is to investigate a suitable path planning algorithm for a multi-agent-based Plug & Produce system that can run online during manufacturing. This is needed since in such systems, resources can move around frequently, making it hard to manually create robot paths. To find a suitable algorithm and verify that it can be used online in a Plug & Produce system, a comparative study between various existing sampling-based path planning algorithms was conducted. Much research exists on path planning carried out offline; however, not so much is performed in online path planning. The specific requirements for Plug & Produce are to generate a path fast enough to eliminate manufacturing delays, to make the path energy efficient, and that it run fast enough to complete the task. The paths are generated in a simulation environment and the generated paths are tested for robot configuration errors and errors due to the target being out of reach. The error-free generated paths are then tested on an industrial test bed environment, and the energy consumed by each path was measured and validated with an energy meter. The results show that all the implemented optimal sampling-based algorithms can be used for some scenarios, but that adaptive RRT and adaptive RRT* are more suitable for online applications in multi-agent systems (MAS) due to a faster generation of paths, even though the environment has more constraints. For each generated path the computational time of the algorithm, move-along time and energy consumed are measured, evaluated, compared, and presented in the article.

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A Classification of Different Levels of Flexibility in an Automated Manufacturing System and Needed Competence

Cited by 7 publications

References 17 publications

A Generic Structure for the Integration of Customized Industrial Gantry Robots into Agents of Plug & Produce Automated Manufacturing System

A Generic Structure for the Integration of Customized Industrial Gantry Robots into Agents of Plug & Produce Automated Manufacturing System

From CAD to Plug & Produce - A generic structure for the integration of standard industrial robots into agents

Sampling-Based Path Planning Algorithm for a Plug & Produce Environment

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A Classification of Different Levels of Flexibility in an Automated Manufacturing System and Needed Competence

Cited by 7 publications

References 17 publications

A Generic Structure for the Integration of Customized Industrial Gantry Robots into Agents of Plug & Produce Automated Manufacturing System

A Generic Structure for the Integration of Customized Industrial Gantry Robots into Agents of Plug & Produce Automated Manufacturing System

From CAD to Plug &amp; Produce - A generic structure for the integration of standard industrial robots into agents

Sampling-Based Path Planning Algorithm for a Plug & Produce Environment

Contact Info

Product

Resources

About

From CAD to Plug & Produce - A generic structure for the integration of standard industrial robots into agents