A simulation-based method to evaluate the impact of product architecture on product evolvability

Luo, Jianxi

doi:10.1007/s00163-015-0202-3

Cited by 30 publications

(21 citation statements)

References 66 publications

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“…On the other hand, efforts to replace the current dominant design by changing the design of the product's structure have only been attempted in the NAND industry. In this study, we define architectural design change as an innovation of a product's structure, which gives the firm a chance to develop new designs and enhance the performance of the product [36]. Note that we include architectural design change as one form of architectural innovation in the NAND flash industry, as seen in Table 1.…”

Section: Dominant Designmentioning

confidence: 99%

The Effect of Incremental Innovation and Switching-Over to Architectural Innovation on the Sustainable Performance of Firms: The Case of the NAND Flash Memory Industry

2019

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This paper presents an empirical study that shows the relationship between innovation activities and the sustainable performance of firms in terms of market share and profit. While previous studies of innovation effects have focused on one type of innovation in the industry, such as incremental or radical innovations, the study of both incremental and architectural innovations in the same industry would enrich our understanding of innovation. This study discusses and emphasizes the importance of continuous incremental innovation and how switching-over to architectural innovation affects the sustainable performance of firms in the NAND flash memory industry. A systematic content analysis, comparing the changes in market and profit leadership in terms of continuous incremental innovation and an introduction of architectural innovation, was performed, and it was concluded that both continuous incremental innovation and switching-over to architectural innovation positively affects the sustainable market and profit leadership of firms. Additionally, architectural innovation reframes the technological lifecycle in the industry and gives a firm a chance to retain and continue its technological leadership by establishing new dominant designs. This study suggests that continuous incremental innovation is very important for high-tech firms, and firms should consider the option of switching-over to architectural innovation instead of the incremental development of current dominant design when the complexity of technology and market is increased in order to have a sustainable advantage.Sustainability 2019, 11, 7105 2 of 20 memory is used for the random access of data, it is faster than the NAND flash memory because it provides sequential access to data. However, the structure of the NAND flash is simpler than that of the NOR flash, so it is more convenient and inexpensive to increase its density. Therefore, the NAND type flash is used for the storage of data, and the NOR flash is used for the storage of codes in general [3]; eventually, the NAND flash dominated the flash industry.Since the inception of the flash memory market in the 1980s, the NOR flash memory has been the dominant design and it accounted for 91% of total flash memory revenue in 2000. However, in 2005, NAND flash revenue surpassed that of the NOR flash for the first time due to the emergence of mobile electronics such as cell phones, MP3 players, memory cards and digital cameras. Since then, the NAND flash market has grown significantly, accounting for 53.8 billion USD in sales in 2017 [5]. In 2013, Samsung was able to successfully introduce a Vertical NAND (VNAND) flash to the market in order to overcome scaling issues and tried to lead the architectural innovation by changing the dimensional design of NAND flash technology from 2D to 3D. Competitors followed the development of the VNAND flash memory and the VNAND flash market was expected to exceed the planar NAND flash market in 2017 [5]. The history and characteristics of the dominant design in the flash...

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Section: Dominant Designmentioning

confidence: 99%

The Effect of Incremental Innovation and Switching-Over to Architectural Innovation on the Sustainable Performance of Firms: The Case of the NAND Flash Memory Industry

2019

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“…Zhang et al, [27] constructed a simulation model of development tasks under the influence of multiple uncertain conditions. Luo [28] evaluated the impact of product architecture on evolvability using simulation methods. Karniel et al, [29] constructed a DSM that reflects changes in the product development process and proposed a product development process management method based on multi-level modeling and simulation.…”

Section: Literature Reviewmentioning

confidence: 99%

Rework Quantification and Influence of Rework on Duration and Cost of Equipment Development Task

2018

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Rework is a sub-task within equipment development tasks that is revised after initial completion to meet task requirements. Some sub-tasks require multiple rework iterations due to their uncertainty and complexity, or the technology and process needs of the overall task, resulting in inefficient task implementation and resource wastage. Therefore, studying the impact of rework iterations on the duration and cost of development tasks is worthwhile. This study divides rework into foreseeable and hidden types and uses several methods to express and quantify their parameters. The main influencing factors in rework iterations—the uncertainty and complexity of the development task—are quantitatively analyzed. Then, mathematical and mapping models of the dependence between sub-tasks, uncertainty, complexity, and rework parameters are established. The impacts of rework type and rework parameters on the duration and cost of equipment development tasks are analyzed via simulation based on the design structure matrix (DSM). Finally, an example is used to illustrate the influence of different rework types and rework parameters on development tasks’ duration and cost. The results show that the duration and cost of development tasks are greater, their volatility range is wider, and the distribution is more dispersed when both foreseeable and hidden rework are considered.

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“…This approach to decision-making is in line with the view that decision-makers may prefer to rely on heuristic rules to achieve desired levels of performance when operating under complex and uncertain environments (Simon, 1972). Flexibility is deemed as an emerging concept to improve the expected economic performance of engineering systems, as shown in many studies and industry sectors like aerospace, automotive, manufacturing, real estate, oil and gas, and transportation (Alp & Tan, 2008;Chen & Yuan, 1999;de Weck et al, 2004;Jain et al, 2013a;Jiao, 2012;Koh et al, 2013;Luo, 2015;Nilchiani & Hastings, 2007;Ross et al, 2008;Subrahmanian et al, 2015;Suh et al, 2007).…”

Section: Flexibility/real Options Analysismentioning

confidence: 99%

Strategic real option and flexibility analysis for nuclear power plants considering uncertainty in electricity demand and public acceptance

2017

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Nuclear power is an important energy source especially in consideration of CO2 emissions and global warming. Deploying nuclear power plants, however, may be challenging when uncertainty in long-term electricity demand and more importantly public acceptance are considered. This is true especially for emerging economies (e.g., India, China) concerned with reducing their carbon footprint in the context of growing economic development, while accommodating a growing population and significantly changing demographics, as well as recent events that may affect the public's perception of nuclear technology. In the aftermath of the Fukushima Daiichi disaster, public acceptance has come to play a central role in continued operations and deployment of new nuclear power systems worldwide. In countries seeing important long-term demographic changes, it may be difficult to determine the future capacity needed, when and where to deploy it over time, and in the most economic manner. Existing studies on capacity deployment typically do not consider such uncertainty drivers in long-term capacity deployment analyses (e.g., 40+ years). To address these issues, this paper introduces a novel approach to nuclear power systems design and capacity deployment under uncertainty that exploits the idea of strategic flexibility and managerial decision rules. The approach enables dealing more pro-actively with uncertainty and helps identify the most economic deployment paths for new nuclear capacity deployment over multiple sites. One novelty of the study lies in the explicit recognition of public acceptance as an important uncertainty driver affecting economic performance, along with long-term electricity demand. Another novelty is in how the concept of flexibility is exploited to deal with uncertainty and improve expected lifecycle performance (e.g. cost). New design and deployment strategies are developed and analyzed through a multistage stochastic programming framework where decision rules are represented as non-anticipative constraints. This approach provides a new way to devise and analyze adaptation strategies in view of long-term uncertainty fluctuations that is more intuitive and readily usable by system operators than typical solutions obtained from standard real options analysis techniques, which are typically used to analyze flexibility in large-scale, irreversible investment projects. The study considers three flexibility strategies subject to uncertainty in electricity demand and public acceptance: 1) phasing (or staging) capacity deployment over time and space, 2) onsite capacity expansion, and 3) life extension. Numerical analysis shows that flexible designs perform better than rigid optimal design deployment strategies, and the most flexible design combining the above strategies outperforms both more rigid and less flexible design alternatives. It is also demonstrated that a flexible design benefits from the strategies of phasing and capacity expansion most significantly across all three strategies studied. The results provide...

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A simulation-based method to evaluate the impact of product architecture on product evolvability

Cited by 30 publications

References 66 publications

The Effect of Incremental Innovation and Switching-Over to Architectural Innovation on the Sustainable Performance of Firms: The Case of the NAND Flash Memory Industry

The Effect of Incremental Innovation and Switching-Over to Architectural Innovation on the Sustainable Performance of Firms: The Case of the NAND Flash Memory Industry

Rework Quantification and Influence of Rework on Duration and Cost of Equipment Development Task

Strategic real option and flexibility analysis for nuclear power plants considering uncertainty in electricity demand and public acceptance

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