Risk Assessment Approach Research Articles

A Takeover Risk Assessment Approach Based on an Improved ANP-XGBoost Algorithm for Human–Machine Driven Vehicles

A Takeover Risk Assessment Approach Based on an Improved ANP-XGBoost Algorithm for Human–Machine Driven Vehicles

Vulnerability status and efficacy of potential conservation measures to reduce tuna fishery bycatch of the Critically Endangered East Pacific leatherback turtle Dermochelys coriacea

Industrial tuna and artisanal fisheries targeting multiple species in the eastern Pacific Ocean (EPO) interact with the Critically Endangered East Pacific (EP) leatherback turtle Dermochelys coriacea. In 2021, a revised Inter-American Tropical Tuna Commission (IATTC) resolution on sea turtles aimed to reduce sea turtle bycatch in EPO industrial tuna fisheries and ensure their safe handling and release. A new ecological risk assessment approach—Ecological Assessment for the Sustainable Impacts of Fisheries (EASI-Fish)—was used to assess vulnerability status and to better understand the potential efficacy of 70 scenarios that compared simulated conservation and management measures (CMMs) for EPO industrial (purse-seine and longline) and artisanal (longline and gillnet) fisheries to the status quo in 2019. In 2019, a fishing mortality proxy (F̃2019) and the breeding stock biomass per recruit (BSR2019) exceeded precautionary biological reference points (F80% and BSR80%), classifying the stock as ‘most vulnerable’. Industrial and artisanal longline fisheries had the highest impacts because they had the highest areal overlap with the modelled EP leatherback distribution. Of the 70 CMM scenarios, 42 resulted in significant improvements in vulnerability status (i.e. to ‘least vulnerable’). The use of large circle hooks, finfish bait, and best handling and release practices each decreased vulnerability; however, the most effective scenarios involved using these 3 measures in concert. The benefits predicted from EASI-Fish for CMM scenarios assume full compliance and attaining the modelled levels of efficacy, our modelling provides stakeholders with evidence-based recommendations to address key threats to EP leatherback turtles to improve their conservation status by reducing fishing impacts.

Risk management in safety standards and environmental management issues of housing construction

At present, the threat of technogenesis is not weakening despite the measures taken to reduce the levels of negative impact on the environment. In this regard, the authors analyze the standardization of risk management as an effective tool for monitoring the safety of not only design decisions in housing construction, but also any economic activity. The article discusses the safety aspects set out in Russian standards (GOSTs) and international guidelines. The analyzed regulatory documentation answers the question of how to achieve an acceptable level of risk. The basic concepts of risk assessment are given. There are positive changes in state standards in the safety area. Federal Law N7 regulates the leadership of the employer, and not his responsibility. As part of the improvement of environmental management for housing construction, the use of certain penalties, interest fines and forfeits looks quite natural. The main goal of the international standard ISO 14001 is not to point out the need for managers to have leadership qualities as the main factor in ensuring environmental safety for the construction industry, but to form a responsible attitude towards the environment and natural resources as the most important asset of economic activity. The article raises the issue that risk analysts cannot be fully guided by domestic standards due to their lack of development and inconsistency with the universal international documents ISO 31000:2018 "Risk management - Guidelines" and ISO 14001:2016 "Environmental management systems". A special risk assessment approach should be developed that describes the interaction of various scenarios, which will provide an increased environmental and economic effect in the field of housing construction safety.

Design of floating wind turbine gearboxes using Gaidai risk assessment method

Generating renewable energy sources, rather than relying on world’s finite natural resources, becoming now increasingly crucial as world agenda focuses on climate issues. System’s high-dimensionality, along with nonlinear cross-correlations between various floating wind turbine mechanical parts, subjected to environmental wind and wave-induced loads, are not always easily handled by traditional risk assessment approaches, dealing with complex environmental energy systems. Empirical bending moments of drivetrain, have been produced using SIMPACK (Multibody Simulation Method), based on in situ wind loads. The aim of this study was to benchmark novel lifetime assessment approach for green energy systems.

Proceedings of the 2023 Viral Clearance Symposium, Session 8: Cell Banks, Advanced Technologies (ATMPs, NGS).

The Cell Banks, Advanced Technologies (ATMPs, NGS) session at the 2023 Viral Clearance Symposium (VCS) focused on the assurance of high virus safety profiles of advanced technology medicinal products (ATMPs) by implementation of advanced virus detection methods using rapid and sensitive technologies, such as next-generation sequencing (NGS). All presentations in this session made the need to replace in vivo testing for viruses by new technologies that have been demonstrated to be incomparably broad in their detection capabilities and can even detect unknown viruses. An evaluation of historical data collected by the Consortium on Adventitious Agent Contamination in Biomanufacturing (CAACB) from their members' in vivo and in vitro adventitious virus test experience as well as on using NGS was presented. The data convincingly supported the necessity to replace in vivo testing with faster, broader, more sensitive, more accurate, and more specific virus detection methods. Additionally, a collaborative study-initiated by the CAACB-with the goal to revisit traditional adventitious agent testing by using targeted NGS to replace in vivo and in vitro tests for well-known and broadly used Chinese hamster ovary (CHO) cells was presented, including the planned risk-assessment approach using prior knowledge and historical data. Overall, this session demonstrated that the use of new virus detection methods, such as NGS, represents a great opportunity to provide sufficient viral safety margins, specifically, for ATMPs, where downstream virus clearance is not possible. This path forward is also supported by the final ICH Q5A(R2) guideline.

Determination of High Risks and Elimination of Possible Risks in the Winding Section of an Energy Company Using the Fine-Kinney Method

In our country, risk assessment and risk analysis have been made mandatory in the workplaces by the relevant regulations of the Law No. 6331. However, despite this, potential hazards cannot be avoided both in industry and workplaces. Predicting what kind of dangers employers and employees may be exposed to in industrial companies is one of the important difficulties encountered. For this reason, it is one of the most important procedures to make a correct risk assessment and to identify, prevent and control Occupational Health and Safety (OHS) risks. One of the many techniques used for OHS risk assessment is the Fine-Kinney model. Most Fine-Kinney-based risk assessment approaches can take into account the relative importance of risk parameters. An improved Fine-Kinney occupational risk assessment approach is proposed in the study. In order to demonstrate the feasibility of the proposed approach, risk values and risk avoidance values have been systematically calculated in all parts of a power plant. A case study was conducted on the bobbin winding unit (Coiling), hazards were identified and measures were presented to eliminate and/or minimize the risk according to the results of the risk analysis.

An Integrated Autonomous Dynamic Navigation Approach toward a Composite Air-Ground Risk Construction Scenario.

Unmanned transportation in construction scenarios presents a significant challenge due to the presence of complex dynamic on-ground obstacles and potential airborne falling objects. Consequently, the typical methodology for composite air-ground risk avoidance in construction scenarios holds enormous importance. In this paper, an integrated potential-field-based risk assessment approach is proposed to evaluate the threat severity of the environmental obstacles. Meanwhile, the self-adaptive dynamic window approach is suggested to manage the real-time motion planning solution for air-ground risks. By designing the multi-objective velocity sample window, we constrain the vehicle's speed planning instructions within reasonable limits. Combined with a hierarchical decision-making mechanism, this approach achieves effective obstacle avoidance with multiple drive modes. Simulation results demonstrate that, in comparison with the traditional dynamic window approach, the proposed method offers enhanced stability and efficiency in risk avoidance, underlining its notable safety and effectiveness.

CYBERSECURITY RISK ASSESSMENT IN BANKING: METHODOLOGIES AND BEST PRACTICES

Cybersecurity risk assessment in banking is the process of identifying, analyzing, and evaluating the cyber threats and vulnerabilities that may affect the confidentiality, integrity, and availability of the information systems and data of banks and their customers. Cybersecurity risk assessment in banking helps banks to prioritize and implement appropriate controls and measures to mitigate the cyber risks and to comply with the relevant regulations and standards. This study focusses on identifying effective risk assessment strategies, highlighting how they can be adapted and applied in various banking environments, especially in developing economies like Nigeria. As the banking industry continues to evolve in the digital era, the significance of robust cybersecurity measures cannot be overstated. This paper delves into the critical domain of Cybersecurity Risk Assessment in Banking, exploring various methodologies and best practices employed to safeguard financial institutions against evolving cyber threats. The dynamic landscape of cyber risks faced by banks, ranging from sophisticated malware and phishing attacks to insider threats and system vulnerabilities are examined. The paper provides an in-depth analysis of established and emerging methodologies for conducting effective cybersecurity risk assessments in the banking sector. It explores quantitative and qualitative risk assessment approaches, threat modeling, and scenario analysis, shedding light on their respective strengths and limitations. Moreover, the document highlights the importance of aligning risk assessment methodologies with industry regulations and compliance standards to ensure a comprehensive and regulatory-compliant cybersecurity framework. Best practices for cybersecurity risk management in banking are scrutinized, emphasizing the integration of proactive threat intelligence, continuous monitoring, and incident response planning. The role of advanced technologies, including artificial intelligence and machine learning, in enhancing the efficiency of risk assessment processes is also discussed. Furthermore, the paper addresses the human element in cybersecurity, emphasizing the significance of training and awareness programs to mitigate risks associated with human error and social engineering attacks. By synthesizing insights from industry practices, regulatory guidelines, and technological advancements, this paper offers a comprehensive guide for banking professionals, cybersecurity practitioners, and policymakers involved in fortifying the resilience of financial institutions against cyber threats. Ultimately, the research aims to contribute to the ongoing discourse on cybersecurity risk assessment in banking, providing actionable insights to navigate the complex landscape of digital risks and ensuring the continued trust and security of the financial ecosystem.
 Keywords: Cybersecurity; Risk Assessment; Banking; Methodologies; Cyber Threat; Artificial Intelligence; Best Practices

In-depth mechanistic analysis including high-throughput RNA sequencing in the prediction of functional and structural cardiotoxicants using hiPSC cardiomyocytes

ABSTRACT Background Cardiotoxicity remains one of the most reported adverse drug reactions that lead to drug attrition during pre-clinical and clinical drug development. Drug-induced cardiotoxicity may develop as a functional change in cardiac electrophysiology (acute alteration of the mechanical function of the myocardium) and/or as a structural change, resulting in loss of viability and morphological damage to cardiac tissue. Research design and methods Non-clinical models with better predictive value need to be established to improve cardiac safety pharmacology. To this end, high-throughput RNA sequencing (ScreenSeq) was combined with high-content imaging (HCI) and Ca2+ transience (CaT) to analyze compound-treated human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Results Analysis of hiPSC-CMs treated with 33 cardiotoxicants and 9 non-cardiotoxicants of mixed therapeutic indications facilitated compound clustering by mechanism of action, scoring of pathway activities related to cardiomyocyte contractility, mitochondrial integrity, metabolic state, diverse stress responses and the prediction of cardiotoxicity risk. The combination of ScreenSeq, HCI and CaT provided a high cardiotoxicity prediction performance with 89% specificity, 91% sensitivity and 90% accuracy. Conclusions Overall, this study introduces mechanism-driven risk assessment approach combining structural, functional and molecular high-throughput methods for pre-clinical risk assessment of novel compounds.

Ecotoxicity and Risk to Zooplankton of a Novel Insecticide Used in Rice Paddies in a Simulated Ecosystem.

Diamide insecticides are widely used in rice paddies and pose a potential threat to aquatic organisms. However, the risk research related to their application in major rice-producing areas is very limited, especially mesocosm research to simulate the impact on aquatic ecosystems of long-term exposure, as well as exposure analysis based on local models and local scenarios. To assess potential risks from a novel diamide insecticide (tetrachlorantraniliprole) to aquatic nontarget organisms in the field over long-term exposure, an outdoor mesocosm study was performed, and the environmental concentrations were predicted by the multimedia paddy-pond model (TOPRICE). The mesocosm experiment showed that tetrachlorantraniliprole mainly stayed in the aqueous phase after entering the water body. Although the chemical dissipated quickly in the aqueous phase (half-life of 0.79-1.5 days), it showed toxic effects on zooplankton communities. Cladocerans, represented by Simocephalus vetulus, were most sensitive to tetrachlorantraniliprole stress. Significant short-term toxicity to cladocerans occurred in all treatment groups, but all recovered within 8 weeks except for the highest concentration group (30.0 µg /L). Based on the ecological recovery results, 7.74 µg tetrachlorantraniliprole/L (nominal concentration, 10.0 µg /L) is suggested to be the no-observed-ecological-adverse-effect concentration (NOEAEC) for the zooplankton community. When this NOEAEC was compared with predicted environmental concentrations (PECs; the PECs in natural ponds simulated by the TOPRICE model for 148 application scheme combinations in major rice-producing areas), a relatively high risk of applying tetrachlorantraniliprole during the rice tillering stage was found. The present study makes a positive contribution to the hypothesis that the current Tier 1 approaches for global acute risk assessment have a sufficient protective effect for assessing the risk of tetrachlorantraniliprole to aquatic organisms. Also, the present results should help us to gain a fuller understanding of the ecological risk of diamide insecticides in aquatic ecosystems and their rational application schemes. Environ Toxicol Chem 2024;43:429-439. © 2023 SETAC.

Applying a risk assessment guided evaluation for verifying comprehensive two-dimensional gas chromatography to analyse complex pharmaceuticals

The reliability of analytical results is critical and indispensable when applied in regulated environments such as the pharmaceutical industry. Therefore, analytical workflows must be validated. However, validation guidelines are often designed for quantitative targeted analysis and rarely apply to qualitative untargeted approaches. In this study, we employ a risk assessment approach to identify critical parameters which might influence the qualitative results derived by online derivatisation — comprehensive two-dimensional gas chromatography coupled to a high-resolution time-of-flight mass spectrometer (GC × GC-HR-ToF–MS) for the analysis of the active pharmaceutical ingredient (API) sodium bituminosulfonate (SBS). To show the complexity and feasibility of such an approach, we focus on investigating three potential risk factors: sample preparation, vapourability, and the thermal stability of sulfonates. Through the individual evaluation of these potential risk factors due to the application of sample preparation approaches and thermal gravimetric analysis (TGA), we demonstrate the high derivatisation efficiency and repeatability of the online derivatisation method and confirm the absence of derivatisation-induced side reactions. In addition, we also show the potential thermal instability of an incompletely derivatised API. To address the limitation of these individual assessments, we applied a holistic evaluation step with negative electrospray ionisation Fourier transform ion cyclotron resonance mass spectrometry (ESI( −) FT-ICR MS) as an orthogonal technique. This confirms that most of the API is detected via the presented GC-based method. Thereby, we demonstrated the practical feasibility of the risk assessment-based approach to ensure the validity of the qualitative data for a complex untargeted method.Graphical

Quantitative health risk assessment of microbial hazards from water sources for community and self-supply drinking water systems

In low and medium income countries (LMIC) drinking water sources (wells and boreholes) often contain a high number of pathogenic microorganisms, that can pose significant human and environmental health risks. In this study, a quantitative microbial risk assessment approach based on existing literature was conducted to evaluate and compare the quantitative health risks associated with different age groups using various drinking water supply systems. Results showed that both community-supply and self-supply modes exhibit similar levels of risk. However, the self-supply water source consistently showed higher risks compared to the community-supply one. Borehole water was found to be a more suitable option than well water, consistently showing between 5 and 8 lower health risks for E. coli and fecal coliform levels, respectively. The sensitivity analysis further showed the importance of prioritizing the reduction of E. coli concentration in well water and fecal coliform concentration in borehole water. This study offers a fresh perception on quantifying the impact of exposure concentration and age groups, shedding light on how they affect environmental health risks. These findings provide valuable insights for stakeholders involved in the management and protection of water sources.

A botanical reference set illustrating a weight of evidence approach for skin sensitization risk assessment

Recent years have seen an increase in the use of botanicals and natural substances (BNS) in consumer products such as cosmetics and household care products. Most work conducted to date to assess botanicals for human safety has focused their use as dietary supplements and thus on systemic toxicity. However, the induction of skin sensitization is a possible adverse effect of natural products in particular those that come into skin contact, especially for cosmetics that remain on the skin and are not rinsed off following use. Assessments of BNS ingredients are often challenging for a number of reasons: the BNS are complex mixtures that can be of mostly unknown composition; the composition can be highly variable even within the same plant species and dependent on how processed; the physical form of the BNS raw material can vary from a highly concentrated powdered extract to a liquid extract containing only a small percentage of the BNS; testing of the BNS raw materials in New Approach Methods (NAM) has uncertainty as these methods are often not developed or validated for complex mixtures. In this study, a reference set of 14 selected BNS which span the range of skin sensitization potential was complied. These data were used in a Weight of Evidence (WoE) approach to evaluate their skin sensitization potential with each of the data rich BNS being classified as either having strong evidence of inducing skin sensitization based on human topical use history, animal data, clinical data, composition data and NAM data, or having some but more limited (weak) evidence of inducing skin sensitization, or having strong evidence of no skin sensitization potential. When available data have sufficient potency related information, sensitization potency assessment is also provided based on WoE, classifying these BNS as either strong, moderate, or weak sensitizers, or non-sensitizers. An outline for a BNS skin sensitization risk assessment framework is proposed starting with exposure-based waiving and WoE assessment for higher exposures. In addition to demonstrating the application of the WoE approach, the reference set presented here provides a set of ‘data rich’ botanicals which cover a range of sensitization potencies that could be used for evaluating existing test methods or aid in the development of new predictive models for skin sensitization.

Importance and Benefits of Green Audits to Education Institutions and Industrial Sectors

Green auditing is a vital process that ensures the diversity of plants on an organization's campus, reducing ecological pollution and soil destruction. It is beneficial intended for biodiversity protection, landscape management, irrigation/economic water utilization, and maintaining natural topography. Green audits are conducted at educational institutions and industrial sectors using the National Building Code (NBC) Part 11 - A 360° Risk Assessment Approach to Sustainability checklist. The importance of green auditing lies in its ability to create an eco-friendly environment and encourage green initiatives was studied at Nehru Arts and Science College, Coimbatore, Tamil Nadu, India. The results revealed that the campus has sufficient number of flora and fauna and established various gardens such as terrace, herbal, kitchen, zodiac, and decorative gardens. All the plants were labelled properly with common and botanical names and used biofertilizers, organic and green manures for the cultivation of plants. Agrochemicals and chemical fertilizers were minimally used to save the soil health and to protect the ecosystem from soil and water pollutions. The benefits of green audit included understanding the organization's internal and external green campus inspection and execution procedures, creating data on plant quantities, recommending biofertilizers, conserving economically valuable, rare, and endangered species, documenting rainwater collection systems, water reservoirs, percolation ponds, and irrigation technologies to the plants were well understood by the Oragnization with respect to the green audit.

Risk assessment approach for tunnel collapse based on improved multi-source evidence information fusion

Risk assessment approach for tunnel collapse based on improved multi-source evidence information fusion

Anomaly detection in trade declarations using deep learning techniques: A risk-assessment approach to identify misclassification and incorrect valuation

In Hong Kong, merchandise trade statistics are compiled based on the commodity information given on the trade declarations submitted by traders. Due to the complexity of the standardised commodity classification system (i.e. Hong Kong Harmonized System, or HKHS in short), there are often reporting errors, especially in the commodity codes and quantities. With around 20 million declarations received annually, the availability of this big data source motivates us to adopt deep learning techniques to detect the reporting errors. This paper proposes a mechanism consisting of three deep learning models for checking the commodity code, quantity and value, which offers an end-to-end solution to data quality assurance for declarations. The results show that the proposed mechanism could enhance the accuracy of error detection, which is conducive to improving the quality of trade statistics. With the use of text analytics techniques, the mechanism could fully utilise free-text commodity descriptions declared by traders to check the accuracy of the declared information comprehensively. It also overcomes some limitations of the traditional rule-based models. The whole study demonstrates the potential of using deep learning approach in quality assurance of existing statistical systems for official statistics.

Risk management behaviour in digital factories: the influence of technology and task uncertainty on managerial risk responses

PurposeThis study aims to advance a behavioural approach towards understanding how managerial perception impacts the enactment of responses to risk management during the implementation of digital technologies in industrial operations and supply chains. The purpose is to investigate the influence of (digital) technology and task uncertainty on the risk perception of managers and how this impacts risk responses adopted by managers.Design/methodology/approachFollowing an exploratory theory elaboration approach, the authors collected more than 80 h of interview material from 53 expert interviews. These interviews were conducted with representatives of 46 German companies that have adopted digital technologies for different industrial applications within manufacturing, assembly and logistics processes.FindingsThe findings provide nuanced insights on how individual and combined sources of uncertainty (technology and task uncertainty) impact the perception of decision makers and the resulting managerial responses adopted. The authors uncover the important role played by the interaction between digital technology and human being in the context of industrial operations. The exploratory study shows that the joint collaboration between humans and technologies has negative implications for managerial risk responses regardless of positive or negative perception, and therefore, requires significant attention in future studies.Research limitations/implicationsThe empirical base for this study is limited to German companies (mainly small and medium size). Moreover, German culture can be characterised by a high uncertainty avoidance and this may also limit the generalizability of the findings.Practical implicationsManagers should critically revise their perception of different types of digital technologies and be aware of the impact of human-machine interaction. Thereby, they should investigate more systematic approaches of risk identification and assessment.Originality/valueThis paper focuses on the managerial risk responses in the context of digitalisation projects with practical insights of 53 expert interviews.

Prediction and assessment of xenoestrogens mixture effects using the in vitro ERα-CALUX assay.

Introduction: Many natural or synthetic compounds used in foods, dietary supplements, and food contact materials (FCMs) are suspected endocrine disruptors (EDs). Currently, scientific evidence to predict the impacts on biological systems of ED mixtures is lacking. In this study, three classes of substances were considered: i) phytoestrogens, ii) plant protection products (PPP) and iii) substances related to FCMs. Fourteen compounds were selected based on their potential endocrine activity and their presence in food and FCMs. Methods: These compounds were evaluated using an in vitro gene expression assay, the ERα-CALUX, to characterize their responses on the estrogen receptor alpha. Cells were exposed to fixed ratio mixtures and non-equipotent mixtures of full and partial agonists. The concentration-response curves measured for the three classes of compounds were characterized by variable geometric parameters in terms of maximum response (efficacy), sensitivity (slope) and potency (median effective concentration EC50). To account for these variations, a generic response addition (GRA) model was derived from mass action kinetics. Results: Although GRA does not allow us to clearly separate the concentration addition (CA) and independent action (IA) models, it was possible to determine in a statistically robust way whether the combined action of the chemicals in the mixture acted by interaction (synergy and antagonism) or by additive behavior. This distinction is crucial for assessing the risks associated with exposure to xenoestrogens. A benchmark dose approach was used to compare the response of phytoestrogen blends in the presence and absence of the hormone estradiol (E2). At the same time, 12 mixtures of 2-5 constituents including phytoestrogens, phthalates and PPPs in proportions close to those found in food products were tested. In 95% of cases, the response pattern observed showed a joint and independent effect of the chemicals on ER. Discussion: Overall, these results validate a risk assessment approach based on an additive effects model modulated by intrinsic toxicity factors. Here, the CA and IA approaches cannot be distinguished solely based on the shape of the concentration response curves. However, the optimized GRA model is more robust than CA when the efficacy, potency, and sensitivity of individual chemical agonists show large variations.

A new approach for gridded risk assessment of rainfall-triggered flood and landslide hazards over a large region based on coupled flood-landslide modelling and ensemble simulation

The assessment of rainfall-triggered flood and landslide hazards is crucial in mitigating the potential damages to both human lives and property. In this study, we conducted a gridded risk assessment of flood and landslide hazards in Shaanxi Province, utilizing an ensemble simulation of a coupled model. The ensemble simulation intervals of discharges met the observed discharges well at the four hydrological stations, and the global accuracies of landslide modeled results were mostly greater than 0.9. The flood hazard rating was low in most areas while the landslide hazard rating was high in south. The high integrated vulnerability area was mainly concentrated in the central region. Flood risk was low in almost the entire area, while landslide risk was high in south and low in the central and northern regions. The methods proposed in this study provide a new perspective on regional risk assessment.

Developing Flexible Risk Management Systems for Resilience in a Post-pandemic World: Can Lessons from a Makerspace Case Study Support Pacific Island Communities?

Pacific Island communities are facing disruptions to supply chains from natural disasters and a changing global environment, which have become more acute following the COVID-19 pandemic. Further, it has been demonstrated how flexible systems can enhance resilience in low-resource environments, such as adapting to changing consumer needs and minimizing supply chain disruptions. This paper considers how the development of a flexible system for conducting a risk assessment on a product that was developed and manufactured in a Makerspace environment would have application in Pacific Island communities to improve resilience. Using a participative action research (PAR) approach, a traditional product risk assessment is refined through iterative PAR cycles to reconceptualize it into a structured simplified risk process. The resulting product development risk assessment process (PDRAP) demonstrates that it is possible to adapt a detailed systematic risk assessment process, such as hazard and operability analysis (HAZOP), to be more suitable and effective for low-resource situations requiring flexible solutions. The improved process provides greater system flexibility to empower people to develop products which may improve their resilience in an ever changing and complex world. The PDRAP process can improve product design and adaptability which assists safeguarding supply chains from system wide disruptions. With the emergence of Makerspaces in developing countries for supply chain recovery from natural disasters and a changing national strategy, the PDRAP provides communities with a low-resource approach for risk assessment to ensure the safe use of products fabricated using emerging low-volume, rapid prototyping, and manufacturing technology.