An Integrated Open Approach to Capturing Systematic Knowledge for Manufacturing Process Innovation Based on Collective Intelligence

Problem definition: Process innovation is commonly claimed to be a major source of competitive advantage for firms. Despite this perceived influence, it has received substantially less attention than product innovation, and much uncertainty remains about its true association with firm performance. We investigate the relationship between a pharmaceutical firm’s portfolio of manufacturing process innovations and its economic performance. Academic/practical relevance: We uniquely conduct a multidimensional evaluation of a firm’s portfolio of manufacturing process innovations at the product level. This allows a quantitative evaluation of both the relative benefit of the different dimensions of a portfolio as well as the potential complementarities between these in different technological landscapes. Methodology: Through a collaboration with expert patent attorneys, we develop a unique longitudinal data set that combines secondary data and evaluations of a firm’s portfolio of process patents along two key dimensions: novelty and scope. We conduct econometric analyses for a large-scale sample of active pharmaceutical ingredients (APIs) whose product patents have expired and for which process innovation is thus the main source of competitive advantage. Results: We find a positive association between the presence of manufacturing process innovation and firm performance. However, although portfolio’s scope appears to always be beneficial to performance, the effect of novelty alone depends on the ruggedness of the technological landscape: negative in smoother landscapes and positive in more rugged landscapes. Results further suggest that novelty and scope of a portfolio of process innovations are complementary across technological landscapes. Managerial implications: Our results provide important practical insights that can inform the organization and execution of the research and development process across high-technology industries. In particular, although process innovations can be economically beneficial, investing in high-novelty process innovations without a corresponding high scope could jeopardize payoffs, especially in technological landscapes that are relatively smooth.

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Manufacturing Process Innovation-Oriented Knowledge Evaluation Using MCDM and Fuzzy Linguistic Computing in an Open Innovation Environment

Sustainability ◽

10.3390/su9091630 ◽

2017 ◽

Vol 9 (9) ◽

pp. 1630 ◽

Cited By ~ 5

Author(s):

Gangfeng Wang ◽

Xitian Tian ◽

Yongbiao Hu ◽

Richard David Evans ◽

Mingrui Tian ◽

...

Keyword(s):

Open Innovation ◽

Manufacturing Process ◽

Process Innovation ◽

Fuzzy Linguistic ◽

Knowledge Evaluation

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Knowledge-Driven Manufacturing Process Innovation: A Case Study on Problem Solving in Micro-Turbine Machining

Micromachines ◽

10.3390/mi12111357 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1357

Author(s):

Dong Zhang ◽

Gangfeng Wang ◽

Yupeng Xin ◽

Xiaolin Shi ◽

Richard Evans ◽

...

Keyword(s):

Problem Solving ◽

Manufacturing Process ◽

Design Method ◽

Process Innovation ◽

Machining Process ◽

Knowledge Network ◽

Design System ◽

Industrial Sectors ◽

Micro Turbine

Micromachining techniques have been applied widely to many industrial sectors, including aerospace, automotive, and precision instruments. However, due to their high-precision machining requirements, and the knowledge-intensive characteristics of miniaturized parts, complex manufacturing process problems often hinder production. To solve these problems, a systematic scheme for structured micromachining process problem solving and an innovation support system is required. This paper presents a knowledge-based holistic framework that enables process planners to achieve micromachining innovation design. By analyzing innovation design procedures and available knowledge sources, an open multi-source Machining Process Innovation Knowledge (MPIK) acquisition paradigm is presented, including knowledge units and a knowledge network. Further, a MPIK network-driven structured process problem-solving and heuristic innovation design method was explored. Subsequently, a knowledge-driven heuristic design system for machining process innovation was integrated in the Computer-Aided Process Innovation (CAPI) platform. Finally, a case study involving specific process problem-solving and innovation scheme design for micro-turbine machining was studied to validate the proposed approach.

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