Mapping Process Research Articles

MAPEAMENTO DE PROCESSOS NA ENGENHARIA CIVIL: OTIMIZAÇÃO DO MONITORAMENTO E EXECUÇÃO DE PROJETOS

Process mapping in civil engineering is crucial for optimizing project monitoring and execution. It provides clarity on the necessary steps, helping the team better understand their roles and responsibilities. With a clear view of the workflow, bottlenecks can be identified and improvements implemented, increasing efficiency and productivity. Additionally, process mapping facilitates communication between different teams, which is essential in complex projects, and ensures compliance with standards and regulations, minimizing legal risks and enhancing safety. With the rise of digitalization, this practice enables the integration of new technologies, further boosting efficiency. The aim of this research is to encourage the adoption of process culture in civil engineering and expand the range of practical case studies on process mapping. Thus, process mapping is established as an essential tool that not only improves project execution but also promotes a more sustainable and innovative future..

Biologically-informed killer cell immunoglobulin-like receptor gene annotation tool.

Natural killer (NK) cells are essential components of the innate immune system, with their activity significantly regulated by Killer cell Immunoglobulin-like Receptors (KIRs). The diversity and structural complexity of KIR genes present significant challenges for accurate genotyping, essential for understanding NK cell functions and their implications in health and disease. Traditional genotyping methods struggle with the variable nature of KIR genes, leading to inaccuracies that can impede immunogenetic research. These challenges extend to high-quality phased assemblies, which have been recently popularized by the Human Pangenome Consortium. This article introduces BAKIR (Biologically informed Annotator for KIR locus), a tailored computational tool designed to overcome the challenges of KIR genotyping and annotation on high-quality, phased genome assemblies. BAKIR aims to enhance the accuracy of KIR gene annotations by structuring its annotation pipeline around identifying key functional mutations, thereby improving the identification and subsequent relevance of gene and allele calls. It uses a multi-stage mapping, alignment, and variant calling process to ensure high-precision gene and allele identification, while also maintaining high recall for sequences that are significantly mutated or truncated relative to the known allele database. BAKIR has been evaluated on a subset of the HPRC assemblies, where BAKIR was able to improve many of the associated annotations and call novel variants. BAKIR is freely available on GitHub, offering ease of access and use through multiple installation methods, including pip, conda, and singularity container, and is equipped with a user-friendly command-line interface, thereby promoting its adoption in the scientific community. BAKIR is available at github.com/algo-cancer/bakir.

Process Mapping of the Sol-Gel Transition in Acid-Initiated Sodium Silicate Solutions.

Fabricating large-scale porous bioactive glass bone scaffolds presents significant challenges. This study aims to develop formable, in situ setting scaffolds with a practical gelation time of about 10 min by mixing 45S5 bioactive glass with sodium silicate (waterglass) and an acid initiator. The effects of pH (2-11), waterglass concentration (15-50 wt.%), and acid initiator type (phosphoric or boric acid) were examined to optimize gelation kinetics and microstructure. A 10 min gelation time was achieved with boric acid and phosphoric acid at various pH levels by adjusting the waterglass concentration. Exponential and polynomial models were proposed to predict gelation times in basic and acidic environments, respectively. The optical properties of the gels were studied qualitatively and quantitatively, providing insights into gelation kinetics and structure. Acidic gels formed smaller particles in a dense network (pores < 550 nm) with higher light transmittance, while basic gels had larger aggregates (pores ~5 µm) and lower transmittance. As the waterglass concentration decreased, pore size and transmittance converged in both groups. The onset of gelation was detected around 8 min using the derivative of light transmittance. This work identifies the key factors controlling waterglass gelation and their impact on gel structure, enabling the tailored creation of formable, in situ setting bioactive glass bone scaffolds.

Improved Production Process Map and Safety of Millet‐Based Fermented Beverage

ABSTRACTThe present study aimed to develop a standardized process map to produce a microbiologically safe and consumer‐acceptable Brukina beverage. Field interactions and observations were employed for the baseline data, while an improved production process was developed and utilized to produce a Brukina beverage. The microbial safety of the new approach was assessed by determining the total coliform, yeast and mold, as well as Staphylococcus aureus. A consumer preference test was conducted to validate the contribution of the improved and hygienic steps to the overall acceptability. The existing production processes for manufacturing Brukina beverage did not embrace Good Manufacturing Practices (GMPs) and as such, the resultant beverage was contaminated with coliforms and S. aureus. Moreover, the sensory characteristics including taste, mouthfeel, viscosity and overall acceptability, were negatively affected. The inclusion of food safety management practices and efficient production steps has a greater tendency of producing microbiologically safe and market‐acceptable fermented millet‐based beverages while safeguarding consumers’ health and satisfaction.

Genetic polymorphisms and bruxism: A scoping review

BackgroundRecent studies have highlighted the multifactorial nature of bruxism, with behavioral, psychosocial, and physiological factors, including genetic predisposition, contributing to its development. However, the role of genetic markers in determining susceptibility to bruxism remains poorly understood, with limited studies offering significant findings. ObjectivesTo identify the current knowledge to investigate the susceptibility of genetic markers for sleep (SB) and/or awake bruxism (AB). Materials and methodsSeven electronic databases and two grey literature platforms were searched up to January 2024. We included studies that related different types of genes and/or genetic polymorphisms with different types of bruxism, regardless of age or sex of the participants. To be included the study must have described the form of detection of bruxism. ResultsA total of 21 reports were included. Of these, 16 were primary research reports. The remaining five articles consisted of four systematic reviews and a literature review incorporating a systematic mapping process, and network visualization. Within the pool of 16 primary study reports, seven focused on the association of genetic polymorphisms with both SB and AB, while seven concentrated solely on the association with SB. One primary study reported results related to probable AB and one article did not specify the bruxism type. Regarding all the studied genes and polymorphisms, significant association results were obtained for 15 polymorphisms from 11 different genes. Self-reported SB was associated with genes from the serotonergic (5HTR2A) and dopaminergic pathways (DRD2, DRD3, and ANKK1), as well as genes encoding enzymes (COMT and MMP9) and proteins (ACTN3 and ANKK1). Instrumentally reported SB was linked only to the reverse telomerase gene (TERT). Self-reported AB was associated with the ACTN3 and ANKK1 genes. ConclusionThis review identified 30 genes and 56 polymorphisms variations potentially associated with either SB or AB. However, few presented significant results regarding positive associations, mostly acting at neurotransmitter pathways. The authors recommend further studies to determine the susceptibility of genetic markers as a risk factor for bruxism.

Process Approach in a Mining Company: LW Bogdanka S.A. Case Study

This article concerns the management of the Polish mining company Lubelski Węgiel (LW) Bogdanka S.A. The main aim of this paper was to describe the whole process of implementing a process approach to management in one of the most important mining companies in Poland. The objective of the research presented was the incorporation of the process approach in LW Bogdanka S.A. to enhance its management and to improve the effectiveness of its mining process. This paper uses a case study method and presents a practical incorporation of the process approach and its results. The first phase of the proposed solution included building a map of business processes. Then, the research consisted of an analysis of existing processes; the introduction of new solutions, mainly in the field of infrastructure and IT systems; and changing the awareness of key process owners. The motivation for applying this approach was to achieve greater efficiency and continuous improvement in LW Bogdanka S.A. The main results and achievements were not merely limited to the development of a map of processes and subprocesses, but also led to an improvement in organizational structure, changes in approach to company management, a diagnosis of problems in the most important company departments, and the proposal of solutions to them.

Study on hot deformation behavior and dynamic recrystallization mechanism of recycled Al–Zn–Mg–Cu alloy

This study utilized Al–Zn–Mg–Cu alloy chips as raw materials to prepare recycled billets through a solid-state recycling process. Isothermal hot compression tests were conducted using a thermal simulation machine to establish an Arrhenius-type constitutive equation and the hot processing map based on the dynamic materials model. The microstructure of the recycled Al–Zn–Mg–Cu alloy after hot compression was characterized and analyzed using SEM, EBSD, and TEM, exploring the microstructural evolution mechanisms of the recycled alloy at different temperatures and strain rates. The results indicate that the optimal hot deformation parameters for the recycled Al–Zn–Mg–Cu alloy are 300–360 °C at a strain rate of 0.01–0.05 s⁻1 and 400–450 °C at a strain rate of 0.05–0.3 s⁻1. At the same strain rate, as the deformation temperature increases, low-angle grain boundaries gradually disappear, and the grain structure becomes more stable. Dynamic recrystallization replaces dynamic recovery as the dominant mechanism. At the same deformation temperature, low strain rates allow more time for the migration of low-angle grain boundaries, thereby promoting the growth of dynamically recrystallized grains and ultimately forming new, undistorted grains.

Lean process mining: adopting process mining in lean manufacturing for dynamic process mapping and avoiding waste occurrence in real time

Purpose This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing processes. Design/methodology/approach The method is developed based on literature review and in-depth explorative research in value stream mapping and process mining approaches. The proposed LPM framework consists of three phases including as-realized process state, improvement strategies and reengineered process state. Hence, firstly, extracts the as-realized model, measures the identified wastes and identifies the sources of wastes. Secondly, implements prediction-recommendation-prevention strategies. Thirdly, reengineers the process model and measures the improved wastes. Findings It presents the applicability of the proposed approach in (1) online observation of manufacturing process behavior and tracing the process deviations dynamically in real time to identify the sources of waste; (2) avoiding defective products occurring during the production and eliminating the relevant derived wastes including wasted material, wasted energy, waste of labor, excess inventory, increased production lead time and wasted operational costs. Originality/value The practical application of LPM is illustrated through implementing it in a real-life manufacturing case. The outcomes prove the remarkable applicability of this method in lean manufacturing to avoid waste occurrence in the value stream.

Critical Value Reporting Performance Improvement Initiative: A Journey Towards Timely Patient Safety

Abstract Timely reporting of critical values serves as a quality indicator for the National Patient Safety Goal. Since the oncology inpatient unit at our institution has the highest number of critical values and often struggles to meet the targeted goal of timely results acknowledgement, this prompted a performance improvement initiative. By utilizing the Institute for Healthcare Improvement (IHI) Model for Improvement, the study aimed to decrease the time from specimen collection to acknowledgment of a complete blood count critical values (overall TAT). Three key metrics were monitored, including unit turnaround time (time from collection to receipt in laboratory; uTAT), laboratory turnaround time (time from receipt in laboratory to verified results) and timely critical value acknowledgment rate (% acknowledgement within 30 minutes). Quality improvement tools such as process maps and fishbone diagrams were employed, and two areas for improvement were identified. Firstly, it was observed that samples collected by the phlebotomists were delivered in batch to the laboratory via carts. However, samples collected by nurses were sent to the laboratory via a pneumatic tube. Hence, the uTAT varied drastically due to the different delivery methods. Secondly, the mode of alerting providers regarding critical values, which was via telephone calls from telecommunication staff, was deemed disruptive and redundant, as the providers often were already aware of the results from the electronic medical record (EPIC). Two multi-cycle Plan-Do-Study-Act (PDSA) interventions were implemented by a multidisciplinary team. The first focused on sending samples via pneumatic tube. The second PDSA intervention focused on a direct clinician acknowledgment of critical values within EPIC, by creating an auxiliary column on the EPIC patient list. Consequently, the overall TAT decreased from a median time of 167 minutes in July 2021 to 140 minutes by March 2022 in the oncology inpatient unit, with a sustained result (139 minutes) by October 2023. This reduction was driven by the standardization of pneumatic tube delivery system; the uTAT decreased from a median time of 104 minutes to 46 minutes by March 2022 and remained low at 52 minutes by January 2024. Notably, the rate of timely acknowledgment of critical value results worsened, dropping from 67% to as low as 51 % (March 2022) and improved to 64% by January 2024. It was realized that this unintended consequence was attributed to the decrease in uTAT, leading to more critical value results reported in early morning when there was less staffing. Despite the worsening in timely critical value acknowledgment, the overall TAT showed a discernible reduction. The application of IHI methodology played a pivotal role in expediting result reporting. Subsequent steps will focus on utilizing secure communication channels to augment the success rate of critical values acknowledgment within 30 minutes.

Finding Meaning in Life for Human Flourishing and Wellbeing: A Mixed Method Research Exploring the Benefits, Possibilities and Challenges of the “On Our Journey” Cards

The “On Our Journey” cards are an innovative resource and an accompaniment to live a happy life, helping individuals to identify, express and regulate their feelings, reflect, make healthy choices, validate their values/principles, and calibrate their life compass. The resource presents a process map where one can find meaning in one’s own actions and life and develop positive mental health which may not only change one’s life but create positive energy that will spread to people who play together with the “On Our Journey” cards, creating a sense of wellbeing and peace. The cards were developed by the Happy Life (Relationships are Forever Foundation) in Malta, together with a team of professionals. Through a set of questionnaires answered by participants who attended a three-day workshop training on the use of the “On Our Journey” cards, and a focus group with seven participants, four main themes emerged that explored the possibilities and the challenges of the cards. These are: the search for meaning in life and spirituality, positive mental health, wellbeing, and present-moment awareness. Results highlight the importance of understanding how to use the cards and the importance of being prepared for potentially challenging initial reactions. Mastery of card usage and allowing time to trust in their effectiveness can lead to significant improvements in human flourishing, mental health, well-being, spirituality, self-awareness, and meaning in life. This paper provides a valuable opportunity for educators and professionals to consider integrating the "On Our Journey" cards into their personal lives and professional practices.

An alloy-agnostic machine learning framework for process mapping in laser powder bed fusion

PurposeThis study aims to introduce an image-based method to determine the processing window for a given alloy system using laser powder bed fusion equipment based on achieving the desired melting mode across multiple materials for powder-free specimens. The method uses a convolutional neural network trained to classify different track morphologies across different alloy systems to select appropriate printing settings. This method is intended for the development of new alloy systems, where the powder feedstock may be unavailable, or prohibitively expensive to manufacture.Design/methodology/approachA convolutional neural network is designed from scratch to identify the 4 key melting modes that are observed in laser powder bed fusion additive manufacturing across different alloy systems. To increase the prediction accuracy and generalisation accuracy across different materials, the network is trained using a novel hybrid data set that combines fully unsupervised learning with semi-supervised learning.FindingsThis study demonstrates that our convolutional network with a novel hybrid training approach can be generalised across different materials, and k-fold validation shows that the model retains good accuracy with changing training conditions. The model can predict the processing maps for the different alloys with an accuracy of up to 96% in some cases. It is also shown that powder-free single-track experiments are a useful indicator for predicting the final print quality of a component.Originality/valueThe “invariant information clustering” (IIC) approach is applied to process optimisation for additive manufacturing, and a novel hybrid data set construction approach that accounts for uncertainty in the ground truth data, enables the trained convolutional model to perform across a range of different materials and most importantly, generalise to materials outside of the training data set. Compared to the traditional cross-sectioning approach, this method considers the whole length of the single track when determining the melting mode.

Unveiling the bright side and dark side of AI-based ChatGPT : a bibliographic and thematic approach

ABSTRACT The current research endeavour aims to examine the most recent advancements pertaining to AI-powered ChatGPT in scholarly literature. Moreover, this research examines both the positive and negative aspects of ChatGPT utilisation across several sectors including business, research, and society. The data was collected from Scopus, using the Preferred Reporting Items for Systematic and Meta-Analysis (PRISMA) methodology. The process of scientific mapping was carried out, wherein both biblometric and thematic analysis was conducted. The results suggest that there is a significant amount of research being conducted on the subject, particularly in the fields of healthcare and education. Thematic analysis reveals a wide range of research issues, including the examination of the impact of technology on decision-making processes and the utilisation of ChatGPT to address complex business challenges. Theoretical perspectives underscore the significance of ethical deliberations, regulatory structures, interdisciplinary cooperation, and user instruction in the advancement and implementation of Artificial Intelligence systems.

MapGPT: an autonomous framework for mapping by integrating large language model and cartographic tools

ABSTRACT The mapping process generally involves intricate operations, such as symbol design, layout design, and text annotation, demanding a high level of professional expertise. The high requirement for map producers hinders the promotion and widespread adoption of mapping. Consequently, researchers are concentrating on techniques to automate and enhance the intelligence of the mapping process. For example, some studies attempt to train deep learning models for mapping, including methods like map style transfer. However, these approaches typically treat the entire map as a global input and generate a new map as output, lacking the flexibility to consider and control detailed elements within a map. Therefore, in this paper, we propose a large language model-based intelligent mapping framework, termed MapGPT, which can be used for mapping by considering the map as an integration of various map elements. Specifically, multiple professional mapping tools are designed in MapGPT, and each tool is designed to control a corresponding map element. With these tools, a large language model is used to first understand the demand of users based on mere natural language descriptions, and subsequently automatically invoke appropriate tools in sequence to generate a map. Furthermore, by utilizing a memory component to store interaction information, users can interact with MapGPT through conversation to adjust map elements such as color and position. In conclusion, MapGPT offers user-friendly mapping experience, showing potential to be a mapping assistant for professional map producers. A comprehensive demonstration of this framework is provided in a visual case study video, accessible at https://github.com/AGI-GIS/MapGPT.

Study on Hot‐Compressive Deformation Behavior and Microstructure Evolution of 12Cr10Co3MoWVNbNB Martensitic Steel

Herein, to improve the microstructure homogeneity of 12Cr10Co3MoWVNbNB steel for turbine blades after forging, the hot deformation behavior and microstructure evolution of the steel are systematically investigated using a hot‐compression experimental setup under the conditions of 950–1150 °C and strain rate of 0.001–10 s−1. A strain‐compensated constitutive equation is established based on the flow curves and the accuracy of its prediction is verified. By combining hot processing map with microstructure observation, the optimal hot processing window is determined to be 1075–1150 °C and 1–10 s−1, within which the grain size can be refined to 14.24 μm. Electron backscatter diffraction is employed to investigate the microstructural evolution and dynamic recrystallization (DRX) nucleation mechanism of the deformed samples, revealing that discontinuous DRX characterized by strain‐induced grain‐boundary migration is the dominant nucleation mechanism. Additionally, the deformation conditions significantly affect the distribution of dislocation density and local misorientation, as well as the transition from low‐angle grain boundaries to high‐angle grain boundaries, which ultimately lead to the differences in DRX fraction and microstructure.

Process mapping with failure mode and effects analysis to identify determinants of implementation in healthcare settings: a guide.

Generating and analyzing process maps can help identify and prioritize barriers to the implementation of evidence-based practices in healthcare settings. Guidance on how to systematically apply and report these methods in implementation research is scant. We describe a method combining a qualitative approach to developing process maps with a quantitative evaluation of maps drawn from the quality improvement literature called failure mode and effects analysis (FMEA). We provide an outline and guidance for how investigators can use process mapping with FMEA to identify and prioritize barriers when implementing evidence-based clinical interventions. Suggestions for methods and reporting were generated based on established procedures for process mapping with FMEA and through review of original research papers which apply both methods in healthcare settings. We provide case examples to illustrate how this approach can be operationalized in implementation research. The methodology of process mapping with FMEA can be divided into four broad phases: 1) formulating a plan, 2) generating process maps to identify and organize barriers over time, 3) prioritizing barriers through FMEA, and 4) devising an implementation strategy to address priority barriers. We identified 14 steps across the four phases. Two illustrative examples are provided. Case 1 describes the implementation of referrals to chiropractic care for adults with low back pain in primary care clinics. Case 2 describes the implementation of a family navigation intervention for children with autism spectrum disorder seeking care in pediatric clinics. For provisional guidance for reporting, we propose the REporting Process mapping and Analysis for Implementation Research (REPAIR) checklist. Process mapping with FMEA can elucidate barriers and facilitators to successful implementation of evidence-based clinical interventions. This paper provides initial guidance for more systematic applications of this methodology in implementation research. Future research should use a consensus-building approach, such as a multidisciplinary Delphi panel, to further delineate the reporting standards for studies that use process mapping with FMEA.

Process Mapping to Support the Implementation of a Regional Strategy to Address the Opioid Epidemic.

To address the opioid epidemic in Kansas City, Missouri, local health systems sought to implement a referral to peer recovery coaches (PRCs) for clients presenting with opioid use disorder. Client referrals were made primarily through health system emergency departments, where PRCs met clients to facilitate linkages to recovery support for up to twelve months. This study aimed to evaluate and improve program implementation with process mapping at three local health systems. Using a five-phase conceptual framework and three development and implementation domains, providers, administrators, and PRCs were interviewed to identify the process for recognizing clients with opioid use disorders and referring them to PRCs. Serial meetings were held to validate the process maps at three health systems and a distillation of key processes was created to guide future analyses and implementation efforts. A detailed process map for each health system was developed, from which a high-level process map was created to support future implementation efforts. Health system-specific process maps varied, although conceptually coherent elements were identified across each system to diagram a recovery ecosystem to support client referrals to PRCs. By systematically assessing the implementation of the same program across different health systems, critical steps, along with their barriers and facilitators, were identified that can be used to understand the processes of care associated with outcomes and to guide future implementation efforts.

Development of an Automatic Rock Mass Classification System Using Digital Tunnel Face Mapping

To mitigate unforeseen incidents, such as key block failure or tunnel collapse during excavation, an appropriate support pattern that correlates with the geological conditions of the rock mass at the tunnel face should be designed. Rock mass evaluations should be conducted through geological face mapping during the construction phase, alongside predictions based on field investigations during the design phase. When marked discrepancies are identified, it is customary to convene an on-site evaluation involving a committee of experts. This study develops a digital tunnel face mapping system that utilises mobile devices to facilitate online evaluations during the construction phase. This system effectively replaces the traditional on-site field evaluation method. Tunnel face mapping can be promptly accomplished using images captured at the excavation face, enabling rapid analysis. In conjunction with the mapping capabilities, the developed system was designed to digitally store geological information, which includes parameters such as rock strength distribution, the spacing and length of discontinuities observed during the mapping process, as well as data pertaining to weathering and the groundwater conditions of those discontinuities. This information was then correlated with the rock mass rating sheet to automate the determination of ratings for each parameter, ultimately leading to a conclusive classification of the rock mass quality. By employing this system for tunnel face mapping and rock quality evaluation, we significantly reduced the discrepancies in the evaluation results that often arise due to the subjective judgement of geologists, as well as human errors that can occur throughout the rating process.

Bullying Systematic Mapping Review

For the United Nations Educational, Scientific, and Cultural Organization, school violence refers to the power imbalance within a context that educational systems can inhibit or favor. However, violence resulting from the power imbalance is structural and can occur between principals against teachers or teachers against students.At the international level, the term "bullying," proposed by Olweus, is used to refer specifically to violence between students, i.e., between peers in the school environment. Bullying is a complicated problem to study and investigate. Therefore, the approach to the phenomenon through scientific production is helpful to understand how knowledge on the subject has evolved.The objective of this text is to present, through the methodological process of systematic literature mapping, the scientific production on bullying, available in open access and Spanish, susceptible to configuring an updated state of the art. The systematized presentation of the results provides elements and documentary support for future research and advocacy projects on bullying

How well can simple clinical features predict long-term language recovery after left-hemisphere glioma surgery?

Long-term language recovery after left-hemisphere glioma surgery varies substantially across patients. We investigated how well it can be predicted using clinical variables such as the postoperative decline in language processing, tumor grade, resection volume and location, extent of resection, and intraoperative language mapping. Beyond predicting the overall recovery, we examined which domains of language processing are most prone to persistent deficits. Fifty-nine patients with left-hemisphere gliomas completed the Russian Aphasia Test (RAT) before surgery, immediately after surgery, and at follow-up three to seventeen months after surgery. We modeled their average language score (Generalized Aphasia Quotient, GAQ) at follow-up using a cross-validated multiple linear regression and calculated the number of patients showing persistent deficits in each subtest of the RAT. The difference between GAQ scores at follow-up and before surgery was not significant at the group level but varied substantially across patients (mean -1.3%, range -34.2-9.2%). Our best-performing model predicted the follow-up GAQ scores with the mean absolute error of 3.5% (cross-validated R2 = 0.15). A greater decline in language processing immediately after surgery predicted worse recovery, whereas intraoperative language mapping predicted better recovery. Deficits in sentence repetition, verb production, verb and sentence comprehension, and object naming most often persisted at follow-up. The postoperative decline in language processing and intraoperative language mapping explain a substantial amount of variability in long-term language recovery. Verbal working memory and lexical retrieval, particularly that of verbs, are most prone to persistent deficits.

Hot deformation behavior and dynamic recrystallization mechanism of GH2132 superalloy

In order to study the hot deformation and dynamic recrystallization behavior of annealed GH2132 superalloy, this paper conducted hot compression tests of GH2132 superalloy at different temperatures (950°C–1150°C) and different strain rates (0.01/s–10/s) using Thermocmaster Z thermal simulation testing machine, and made an in-depth analysis of recrystallization behavior via electron backscattered diffraction (EBSD). The results indicate that the flow stresses of GH2132 alloy first increase and then decrease at high temperature, among which the curves present a more obvious flow softening at 10/s. Continuous dynamic recrystallization (CDRX) is dominant at high temperature and low strain rate, while discontinuous dynamic recrystallization (DDRX) plays the major role at low temperature and high strain rate. The type of recrystallization has a significant impact on the formation and volume fraction of twinning. In addition, high-temperature constitutive model, hot processing map, and an unified dynamic recrystallization kinetic model of GH2132 superalloy were established. Thus, the optimal range of hot working parameters was obtained. The research results provide guidance for determining the hot working process window of GH2132 superalloy.