Using E-mobility as an Enabler for a Fast and Lean Product Development to Optimize the Return of Engineering with the Example of Lithium-ion Battery

Kampker, Achim; Deutskens, Christoph; Heimes, Heiner Hans; Ordung, Mathias; Haunreiter, Andreas

doi:10.1016/j.procir.2016.05.085

Cited by 7 publications

(6 citation statements)

References 16 publications

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“…For the meat processor, the chip on the live animal enables ‘farm‐to‐fork’ traceability. As such, consistent with Kampker et al (2016) and Tortorella et al (2019), I4.0 facilitates greater supplier involvement in the customer's production process, reduces administrative burdens and speeds up communication. Further, the fruit producer has been able to adapt quickly to emerging customer requirements such as new packaging design.…”

Section: Discussionsupporting

confidence: 56%

“…Finally, since physical and digital technologies are integrated during the product development process, I4.0 facilitates greater supplier involvement (Hozdić, 2015; Santos et al, 2017; Tortorella et al, 2019). The resulting generation and treatment of data and improved connection and traceability facilitate faster and more accurate new product creation and production (Kampker, Deutskens, Heimes, Ordung, & Haunreiter, 2016; Liao, Deschamps, Loures, & Ramos, 2017). This involvement and joint development through I4.0 lead to value co‐creation which is particularly advantageous for resource constrained SMEs who may lack the skills do achieve this alone (Benitez et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

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Innovation in the Agri‐Food sector: Exploiting opportunities for Industry 4.0

et al. 2020

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Agri‐Food producers have a responsibility to provide safe, secure and sustainable food in a world characterized by disruption and increasing intolerance of waste along supply chains. As such, it is critical that they adopt new technologies to ensure efficient and effective management of their responsibility. While Industry 4.0 (I4.0) technologies can underpin process innovation opportunities, there is a gap in research‐based understanding of how they influence innovation practice and outcomes in Agri‐Food. In this paper, we investigate how I4.0, as a set of enabling technologies, influences core process innovation practice and product innovation outcomes in Agri‐Food firms. We present case studies of two Spanish firms processing fresh food products, competing in two important subsectors of the industry, meat and fruit and vegetables. We used secondary material and semi‐structured interviews as data sources. The findings describe how, in the two cases, I4.0 has enabled responses to new customers requirements through process innovations resulting in enhanced functionality, aesthetics and meaning of the delivered products. Our paper contributes a framework identifying for researchers and managers how I4.0 technologies act as enablers of the core innovation processes and competitive outcomes.

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Section: Discussionsupporting

confidence: 56%

Section: Literature Reviewmentioning

confidence: 99%

Innovation in the Agri‐Food sector: Exploiting opportunities for Industry 4.0

et al. 2020

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“…Operation and production management provide the best practices for entrepreneurs to reach their goal within the environment. That is, recognizing the opportunities and constraints that exist allows entrepreneurs to remove waste (Kampker et al , 2016).…”

Section: Resultsmentioning

confidence: 99%

A framework proposition to identify customer value through lean practices

Peralta

Echeveste

Lermen

et al. 2020

JMTM

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PurposeCustomer value is the key to successful innovation management. This task is considered complex and abstract. For this reason, several models have been proposed to that end, among them, Lean approaches. Lean's background has been applied to value identification, providing many benefits. This paper aims at analyzing the practices employed to identify customer value through Lean approaches.Design/methodology/approachThrough a systematic literature review, the main Lean practices for customer value identification were categorized based on five main streams: (1) customer development, (2) customer value, (3) lean product, (4) lean start-up, and (5) lean innovation. These practices were organized into a framework that addresses value identification based on ideation, value prospection, requirements, construction and measurement, and value delivery.FindingsIn total, 33 practices were found to support capturing the value from the customer's perception. Additionally, a discussion is provided on the complementarity and differences between practices.Originality/valueA framework is proposed to integrate the five streams and the corresponding practices for value identification. The results provide mechanisms that can benefit practitioners to better understand the value demanded by customers during innovation management. In fact, practitioners can use the proposed framework to identify value to customers in a holistic way. Academically, the results gather research on customer value and innovation management to contribute with a novel artifact for customer value identification in operations management using Lean approaches. Finally, a future research agenda on value identification is proposed.

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“…At the same time, cars are increasingly connective and become more and more digitised by assistance systems (Gärtner and Heinrich 2018). Especially, the integration of intelligent assistance systems leads to a radical increase in the complexity of parts and car variants (Kampker et al 2016, Krumm et al 2014, resulting in a new complexity in the automotive DCM process. Automotive product life cycles (PLC) amount to about seven years.…”

Section: Challenges Of the Automotive Dcmmentioning

confidence: 99%

Proactive demand and capacity management for automotive logistics using an efficient information model

Temur¹,

Fruhner²,

Klingebiel³

2019

The European Modeling and Simulation Symposium

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The increasing technical complexity of cars and the high number of offered options lead to new challenges in the automotive industry and especially the mid-term demand and capacity management (DCM). This requires a procedural adaptation based upon an efficient information model. In this contribution, the state of the art is analysed for both the DCM process and the underlying information models. Promising concepts for managing the steadily increasing requirements in DCM are deducted, and a modular process kit for the procedural adaptation combined into the concept SmartDCM is introduced. Additionally, a new approach of an efficient information model for managing the increasingly complex information is presented.

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Using E-mobility as an Enabler for a Fast and Lean Product Development to Optimize the Return of Engineering with the Example of Lithium-ion Battery

Cited by 7 publications

References 16 publications

Innovation in the Agri‐Food sector: Exploiting opportunities for Industry 4.0

Innovation in the Agri‐Food sector: Exploiting opportunities for Industry 4.0

A framework proposition to identify customer value through lean practices

Proactive demand and capacity management for automotive logistics using an efficient information model

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