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1. Process Multiplicity and Process Dynamics: Weaving the Space of Possible Paths

   https://doi.org/10.1177/2631787720963138  

   Pentland, Brian_T; Mahringer, Christian_A; Dittrich, Katharina; Feldman, Martha_S; Wolf, Julie_Ryan (September 2020, Organization Theory)

   In research on process organization studies, the concept of multiplicity is widely used, but a fundamental confusion about what process multiplicity means persists. As a result, we miss some of the potential of this concept for understanding process dynamics and process change. In this paper, we define process multiplicity as a duality of ‘one’ and ‘many’, and we conceptualize ‘the many’ as a space of possible paths encompassed by a process. We use the notion of paths to operationalize process multiplicity and make it accessible for empirical research. When we see process as a multiplicity, process change can be understood as expanding, shifting or contracting the space of possible paths. We suggest that this concept of process multiplicity also has implications for a range of other theoretical and practical topics, including standards, standardization and flexibility as well as process replication, management and resilience. 

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2. Theorizing Process Dynamics with Directed Graphs: A Diachronic Analysis of Digital Trace Data

   https://doi.org/10.25300/MISQ/2021/15360  

   Pentland, Brian; Vaast, Emmanuelle; Wolf, Julie Ryan (June 2021, MIS Quarterly)

   null (Ed.)

   The growing availability of digital trace data has generated unprecedented opportunities for analyzing, explaining, and predicting the dynamics of process change. While research on process organization studies theorizes about process and change, and research on process mining rigorously measures and models business processes, there has so far been limited research that measures and theorizes about process dynamics. This gap represents an opportunity for new information systems research. This research note lays the foundation for such an endeavor by demonstrating the use of process mining for diachronic analysis of process dynamics. We detail the definitions, assumptions, and mechanics of an approach that is based on representing processes as weighted, directed graphs. Using this representation, we offer a precise definition of process dynamics that focuses attention on describing and measuring changes in process structure over time. We analyze process structure over two years at four dermatology clinics. Our analysis reveals process changes that were invisible to the medical staff in the clinics. This approach offers empirical insights that are relevant to many theoretical perspectives on process dynamics. 

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3. INVESTIGATION OF MECHANICAL ENGINEERING STUDENTS’ PERCEPTIONS OF DESIGN PROCESS MODELS

   https://doi.org/10.1115/DETC2022-88445  

   Dugan, K.E.; Daly, S.R. (January 2022, Proceedings of the ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference)

   Engineering designers, who are increasingly tasked with solving complex problems, leverage various forms of support to practice and develop their design skills as well as ultimately navigate the complexity of the problems with which they are faced. Design process models are one such form of support, particularly those process models that prescribe how to design. To better understand how process models impact design approaches, this preliminary study analyzed semi-structured interviews—focused on participants’ perceptions of three design process models—with six upper-level mechanical engineering students. Across participants’ responses, we identified eight dimensions used to distinguish the usefulness of each process model: impacts considered, project scope, stakeholder interactions, problem definition, project deliverable, solution novelty, solution type, and process applicability. In addition, participants differentiated the three process models based on iteration and the level of detail within a model. Our findings highlight the importance of accounting for varying interpretations across process model users and suggest that students would benefit from multiple design process models, including process models that recognize society and people in engineering decision-making. 

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4. Investigating a Socially Engaged Design Process Model

   Dugan, K.E.; Daly, S.R.; Michaels, C.; Skerlos, S.J.; Verhey-Henke, A. (January 2022, Proceedings of the American Society for Engineering Education Conference)

   Educators can leverage a variety of process models to scaffold students from beginning designer practices to practices aligned with more experienced designers. The Center for Socially Engaged Design at the University of Michigan developed a Socially Engaged Design (SED) Process Model to explicitly emphasize important aspects of design that are often underemphasized or not included in commonly-used design process model visualizations, including, for example, designers embracing the limitations of their own perspective and acknowledging the power they hold, the benefits of integrating contextual considerations, and the use of prototypes throughout a design process rather than as single phase in a design process. To better understand the role of design process models, broadly, and the perceived value of process models that emphasize the importance of people and context in design work, specifically, we investigated upper-level mechanical engineering students' perceptions of this SED Process Model’s visualization. Our findings from this initial exploratory study showed both variability and several consistent themes in participants’ perceptions, for example, there were several interpretations of relationships between different aspects of the model, iteration in design was salient to all participants, and while this SED Process Model’s visualization does have recommendations, several participants noted it does not specify exactly how to achieve those recommendations. Understanding engineering students’ perceptions of this SED Process Model’s visualization can help us (1) iterate on the process model’s visualization and (2) better understand how to leverage multiple process model visualizations in engineering curricula. 

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5. Process monitoring and control strategies in extrusion-based bioprinting to fabricate spatially graded structures

   AA Armstrong, A Pfeil (April 2021, Bioprinting)

   null (Ed.)

   Extrusion-based bioprinting is the most common printing technology used in regenerative medicine. Despite recent technological advances, a pressing challenge for extrusion printing is low spatial resolution, which limits the functionality of printed constructs. One of the reasons for the low spatial resolution is a lack of process monitoring and control strategies to monitor fabrication and correct for print errors. Few research efforts implement process control and investigate the relationship between extrusion process parameters and printing fidelity. The lack of understanding between process parameters and print results ultimately limits the complexity of the possible structures. For example, fabrication of structures whose topologies vary spatially within the part is not possible without advanced process control. Here we enable fabrication of advanced spatially graded structures by implementing process monitoring and control strategies. We develop material models to better understand the relationship between process parameters and printing outcomes. We also present an experimental procedure to generate a process map that provides insight into the regions of the processing space that produce the desired extrusion features (e.g., width of the filament). After generation of a process map and material models, we implement a process monitoring and control strategy that measures the feature error and intelligently updates the process control inputs to reduce defects and improve spatial fidelity, which will lead to better functionality of the final construct. 

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