Energy and peak-power optimization of existing time-optimal robot trajectories

Riazi, Sarmad; Bengtsson, Kristofer; Bischoff, Rainer; Aurnhammer, Andreas; Wigström, Oskar; Lennartson, Bengt

doi:10.1109/coase.2016.7743423

Cited by 19 publications

(16 citation statements)

References 13 publications

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“…Fysikopoulos et al have taken up this challenge and developed a generalized approach to manufacturing energy efficiency based on a machine-level study [27], while Brizzi et al present a case study on the remote monitoring of robot energy consumption, demonstrating the capability of intelligent applications for managing manufacturing processes [28]. An impressive example for more energy efficiency based on process optimization is presented in [29,30], where an algorithm is introduced that allows reducing energy consumption for industrial robots up to 30% by adapting acceleration and deceleration behavior, without substituting hardware or negative consequences on the production rate.…”

Section: Sustainable Energymentioning

confidence: 99%

More Sustainability in Industry through Industrial Internet of Things?

2018

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Industrial production plays an important role for achieving a green economy and the sustainable development goals. Therefore, the nascent transformation of industrial production due to digitalization into a so-called Industrial Internet of Things (IIoT) is of great interest from a sustainable development point of view. This paper discusses how the environmental dimension of a sustainable development can potentially benefit from the IIoT-focusing especially on three topics: resource efficiency, sustainable energy and transparency. It presents a state of the art literature analysis of IIoT-enabled approaches addressing the three environmental topics. This analysis is compared with the findings of a survey among Chinese industrial companies, investigating the sustainability-related expectations of participants coming along with the implementation of IIoT solutions. China has been chosen as a case study because it brings together a strong industrial sector, ambitious plans regarding industrial digitalization and a high relevance and need for more sustainability. The survey was conducted with the means of a questionnaire which was distributed via email and used for direct on-site interviews. It focused on large and medium sized companies mainly from Liaoning Province and had a sample size of 109 participants.

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Section: Sustainable Energymentioning

confidence: 99%

More Sustainability in Industry through Industrial Internet of Things?

2018

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“…Most papers put forward frameworks that lay the theoretical foundations for more resource-efficient production in a hypothetical Industry 4.0 future, or provide prototypical solutions. Very few of the papers reviewed quantify efficiency potentials ( [40,45]), and these will need to be interpreted carefully, as their relevance and possible potentials will significantly vary in different sectors of application. The presented approach, where the dynamic behavior of robots has been adapted to operate with as little energy as possible, will be highly relevant in the automotive industries, for example, but might not be equally relevant in the chemical or textile industries, as the use of hundreds of robots is not as common there.…”

Section: Discussionmentioning

confidence: 99%

“…• Issues hindering efficient activity scheduling techniques in machine-to-machine communications for more energy efficiency [37]; • workflow for integrating energy data into material flow simulation [38]; • simulation method for energy optimization [39]; and • algorithm adjusting dynamic properties of robots to reduce energy consumption [40].…”

Section: Orchestrationmentioning

confidence: 99%

“…Their algorithm optimizes energy usage by adjusting dynamic properties of the system components and was tested in the powertrain industry [39]. A similar concept, also based on adjusting dynamic properties to reduce their overall energy consumption, was applied on industrial robots in [40], where an algorithm was introduced that allows the robots to reduce their energy consumption by up to 30% by adapting acceleration and deceleration behavior, without substituting hardware or slowing the rate of production. The results they obtained are especially impressive as the proposed solution was validated in an industrial context.…”

Section: Orchestrationmentioning

confidence: 99%

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Industry 4.0 and Climate Change—Exploring the Science-Policy Gap

2018

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The paper aims to explore the gaps and overlaps between statements of intergovernmental organizations (IGOs) working at the intersection of climate change, sustainable energy, and industrial development regarding the role of Industry 4.0 for climate change mitigation and the scientific literature addressing the energy and resource efficiency of Industry 4.0. To fulfill this objective, we conduct a two-tier review of relevant literature from both IGOs as well as academia. The analysis of documents from IGOs shows that Industry 4.0 is strongly associated with energy efficiency potentials that could contribute to climate change mitigation and more sustainable energy use in the industrial sector. Based on a review of the scientific literature, however, the paper concludes that it is currently not possible to validate this assumption and provide concrete figures since analyses providing a more comprehensive picture of potential energy savings, including possible negative effects and rebounds, are lacking. We suggest that these issues be addressed in further research, e.g., through concrete case studies that go beyond the assessment of single Industry 4.0 technologies. Furthermore, efforts should be strengthened to communicate findings from technology-centered research into political strategy-building and decision-making processes and, at the same time, raise awareness in the technological domain for the information needs of policymakers.

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“…During the first years, algorithms to handle product and automation system interaction (Bengtsson et al, 2009), and to visualize complex operation sequences using multiple projections , was developed. Over the years, other use cases have been integrated, like formal verification and synthesis using Supremica (Bergagård and Fabian, 2012), restart support , cycle time optimization (Sundström et al, 2012), energy optimization and hybrid systems (Riazi et al, 2016), online monitoring and control (Theorin et al, 2016), as well as emergency department online planning support . SP is developed as a micro service architecture, where various services interact with each other by sending messages.…”

Section: Sequence Plannermentioning

confidence: 99%

Sequence Planner: Supporting Integrated Virtual Preparation and Commissioning

et al. 2017

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Abstract:It is essential to understand the operation sequences of a production system when designing or changing it. This paper will demonstrate how the software tool Sequence Planner (SP) not only supports this understanding by sequence visualization, but also improves the solution using optimization and verification. SP is a tool for modeling and analyzing automation systems. The tool has been developed since 2007 with an initial focus on supporting engineers when developing control code for programmable logical controllers. Today, SP is a microservice architecture, usable in various areas like runtime control, online monitoring, energy optimization, and even emergency department patient planning. This paper presents a use case at an automotive company, where the operation sequences in a large number of automated robot stations, need to be modified. SP, together with virtual commissioning tools, automates this modification by identifying, optimizing, verifying and simulating operation sequences, and then updates the robot and control programs. This use case demonstrates the strength of SP and its architecture and how it is used for integrated virtual preparation and commissioning.

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Energy and peak-power optimization of existing time-optimal robot trajectories

Cited by 19 publications

References 13 publications

More Sustainability in Industry through Industrial Internet of Things?

More Sustainability in Industry through Industrial Internet of Things?

Industry 4.0 and Climate Change—Exploring the Science-Policy Gap

Sequence Planner: Supporting Integrated Virtual Preparation and Commissioning

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