Complementing lean with quick response manufacturing: case studies

Gómez, J P Fernando; Filho, Moacir Godinho

doi:10.1007/s00170-016-9513-4

Cited by 15 publications

(6 citation statements)

References 48 publications

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“…It empowers companies to anticipate challenges, optimize operations, and stay at the forefront of technological advancements. By fostering innovation, flexibility, and data-driven decision-making, this convergence paves the way for a new era of manufacturing excellence in the dynamic landscape of Industry 4.0 [26,27]. Beyond technological gains, this integration leads to tangible business outcomes, such as increased performance, enhanced quality, and elevated efficiency, which directly contribute to a company's economic viability and competitive edge [28].…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Digital Model Approach for Adaptive Manufacturing Systems

Grznár,

Burganová,

Mozol

et al. 2023

Applied Sciences

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In the current global economy, where rapid changes and constantly shifting market demands define the competitive landscape, adaptive manufacturing systems become essential for businesses striving to remain relevant and efficient. In the context of this growing need, this study focuses on planning as a part of adaptive manufacturing system. This methodology provides a systematic framework that spans from foundational groundwork to meticulous verification and validation phases. By employing advanced simulation techniques, seamless data integration, and process optimization, this methodology ensures the smooth realization of robust and efficient adaptive manufacturing systems. A detailed case study on competency islands showcases the versatility of this approach, demonstrating its efficacy in enhancing manufacturing agility and overall performance. As a significant contribution to the field of smart manufacturing, this methodology offers a structured blueprint for the realization of adaptive manufacturing systems.

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Section: Introductionmentioning

confidence: 99%

A Comprehensive Digital Model Approach for Adaptive Manufacturing Systems

Grznár,

Burganová,

Mozol

et al. 2023

Applied Sciences

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“…These conditions apply pressure on manufacturers to maximize the efficiency of their operations and on manufacturing to meet customers' requirements. In order to achieve this goal, a wide range of methodologies are available, including lean manufacturing (LM), six sigma (SS), the theory of constraints (TOC), quick response manufacturing (QRM), and agile manufacturing (AM), which appear to be amongst the most popular methods across the academic literature [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, lean and agile manufacturing have been analyzed in the literature in progression, in combination, and in isolation [15]. In addition, there are complementary elements in both lean and QRM that have been analyzed in previous research [7,16].…”

Section: Introductionmentioning

confidence: 99%

“…These are [4]: • Quick response manufacturing (QRM) was introduced in 1998 by Suri, and it was derived from the concept of time-based competition (TBC) [8]. QRM answers the challenge of low-volume-high-variety production systems, which required a different approach to process improvement and performance [7]. It reduces the lead time of the provided products to satisfy customers and respond rapidly to the actual demand, which is why it is often used in dynamic production with high variety and customization.…”

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confidence: 99%

“…Characterization of improvement strategies: principles, tools, factors, and target KPIs (own elaboration based on[4][5][6][7]9,11,15,16,19,20,37,41,43,[48][49][50][51][52][53][54][55]). …”

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confidence: 99%

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A Systematic Improvement Model to Optimize Production Systems within Industry 4.0 Environments: A Simulation Case Study

Groten

Gallego-García

2021

Applied Sciences

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The industrial revolutions and their impact on production systems have increased productivity and quality in manufacturing over time. Lean methods have been the driver of the development of production systems from the 1990s to the rise of the fourth industrial revolution, or Industry 4.0. However, many different approaches and methodologies have been described, applied, and discussed for achieving improvements in production systems. As a result, organizations are often confused in regard to the order, the convenience, and the outcomes intended by the different improvement strategies and techniques. This paper provides a systematic sequence of process optimization steps that can be applied to any organization. A conceptual model was built based on the systematic sequence. In addition, a simulation model was built with the goal of representing and quantifying the sequential steps of the conceptual model. The results of the simulation model show a clear improvement in quality, performance, and economic indicators, with the first two steps in the optimization sequence providing critical initial information, while the three last steps served as net contributors to a global production system improvement for demanding market scenarios. Finally, we analyzed the impacts of Industry 4.0 on production systems and developed a methodological sequence to design, select, implement, and control projects, even those that include Industry 4.0 technologies.

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