Challenge For Industry Research Articles

The Utilization of Carbonated Steel Slag as a Supplementary Cementitious Material in Cement.

Carbon emission reduction and steel slag (SS) treatment are challenges in the steel industry. The accelerated carbonation of SS and carbonated steel slag (CSS) as a supplementary cementitious material (SCM) in cement can achieve both large-scale utilization of SS and CO2 emission reduction, which is conducive to low-carbon sustainable development. This paper presents the utilization status of CSS. The accelerated carbonation route and its effects on the properties of CSS are described. The carbonation reaction of SS leads to a decrease in the average density, an increase in the specific surface area, a refinement of the pore structure, and the precipitation of different forms of calcium carbonate on the CSS surface. Carbonation can increase the specific surface area of CSS by about 24-80%. The literature review revealed that the CO2 uptake of CSS is 2-27 g/100 g SS. The effects of using CSS as an SCM in cement on the mechanical properties, workability, volume stability, durability, environmental performance, hydration kinetics, and microstructure of the materials are also analyzed and evaluated. Under certain conditions, CSS has a positive effect on cement hydration, which can improve the mechanical properties, workability, bulk stability, and sulfate resistance of SS cement mortar. Meanwhile, SS carbonation inhibits the leaching of heavy metal ions from the solid matrix. The application of CSS mainly focuses on material strength, with less attention being given to durability and environmental performance. The challenges and prospects for the large-scale utilization of CSS in the cement and concrete industry are described.

Sequence Segmentation of Nematodes in Atlantic Cod with Multispectral Imaging Data.

Nematodes pose significant challenges for the fish processing industry, particularly in white fish. Despite technological advances, the industry still depends on manual labor for the detection and extraction of nematodes. This study addresses the initial steps of automatic nematode detection and differentiation from other common defects in fish fillets, such as skin remnants and blood spots. VideometerLab 4, an advanced Multispectral Imaging (MSI) System, was used to acquire 270 images of 50 Atlantic cod fillets under controlled conditions. In total, 173 nematodes were labeled using the Segment Anything Model (SAM), which is trained to automatically segment objects of interest from only few representative pixels. With the acquired dataset, we study the potential of identifying nematodes through their spectral signature. We incorporated normalized Canonical Discriminant Analysis (nCDA) to develop segmentation models trained to distinguish between different components within the fish fillets. By incorporating multiple segmentation models, we aimed to achieve a satisfactory balance between false negatives and false positives. This resulted in 88% precision and 79% recall for our annotated test data. This approach could improve process control by accurately identifying fillets with nematodes. Using MSI minimizes unnecessary inspection of fillets in good condition and concurrently boosts product safety and quality.

Optimizing the Die-Sink EDM Machinability of AISI 316L Using Ti-6Al-4V-SiCp Electrodes: A Computational Approach

Die-sink electric discharge machining (EDM) is essential for shaping complex geometries in hard-to-machine materials. This study aimed to optimize key input parameters, such as the discharge current, gap voltage, pulse-on time, and pulse-off time, to enhance the EDM performance by maximizing the material removal rate while minimizing the surface roughness, residual stress, microhardness, and recast layer thickness. AISI 316L stainless steel was chosen due to its industrial relevance and machining challenges, while a Ti-6Al-4V-SiCp composite electrode was selected for its thermal resistance and low wear. Using Taguchi’s L27 orthogonal array, this study minimized the trial numbers, with analysis of the variance-quantifying parameter contributions. The results showed a maximum material removal rate of 0.405 g/min and minimal values for the surface roughness (1.95 µm), residual stress (1063.74 MPa), microhardness (244.8 Hv), and recast layer thickness (0.47 µm). A second-order model, developed through a response surface methodology, and a feed-forward artificial neural network enhanced the prediction accuracy. Multi-response optimization using desirability function analysis yielded an optimal set of conditions: discharge current of 5.78 amperes, gap voltage of 90 volts, pulse-on time of 100 microseconds, and pulse-off time of 15 microseconds. This setup achieved a material removal rate of 0.13 g/min, with reduced surface roughness (2.46 µm), residual stress (1518.46 MPa), microhardness (259.01 Hv), and recast layer thickness (0.87 µm). Scanning electron microscopy further analyzed the surface morphology and recast layer characteristics, providing insights into the material behavior under EDM. These findings enhance the understanding and optimization of the EDM processes for challenging materials, offering valuable guidance for future research and industrial use.

North American considerations, strategies, and practices in reducing the sodium content in processed foods.

Most Americans exceed the recommended limit for sodium in their diet, a risk factor for hypertension and cardiovascular disease. Efforts have been made by the food industry and government agencies to reduce the sodium content in foods and encourage the consumption of lower sodium diets. Such efforts, however, are not successful in improving public health when consumers do not accept and consume lower sodium foods. This review article provides an overview of the strategies that have been used by the US food industry to reduce and replace sodium in consumer packaged goods, as well as future sodium reduction strategies and approaches for replacing sodium with potassium salts. Challenges in consumer acceptance regarding the reduction of sodium in foods are also discussed. Because of the widespread consumption of numerous sodium-containing consumer packaged goods, implementing future strategies in various aspects of salt reduction and potassium replacement in foods should have a profound impact on the health of Americans. PRACTICAL APPLICATION: New information is provided herein as it discusses the most current and collective perspectives of major food industry successes and challenges, as well as government strategies to decrease sodium intake. The information provided also addresses future strategies for reducing sodium content in foods, increasing potassium intake, and consumer acceptance of lower sodium foods.

Providing innovative genetic solutions to the future challenges of the poultry industry: extraction of a small-sized Single-nucleotide polymorphism (SNP) panel using factorial design for parentage assignment in a population consisting of pure and hybrid ducks

Providing innovative genetic solutions to the future challenges of the poultry industry: extraction of a small-sized Single-nucleotide polymorphism (SNP) panel using factorial design for parentage assignment in a population consisting of pure and hybrid ducks

Identification of the low resistivity-low contrast (LRLC) gas-bearing pay zones in Shaly sand reservoirs using acoustic data: a case study from the Messinian Abu Madi formation, onshore Nile Delta, Egypt

Detection of the low resistivity-low contrast (LRLC) reservoirs is among the main challenges in the oil industry. In this concern, the LRLC pay zones of the Upper Messinian Abu Madi clastic reservoirs in the onshore Nile Delta Gas fields became a main challenge for significant exploration. This type of reservoirs, including low resistivity-low contrast zones and thin-bedded intervals, are often overlooked using the conventional petrophysical evaluation techniques, especially in the wildcat exploratory wells or highly agitated shoreline depositional environments like the Nile Delta of Egypt. These hidden low contrast reservoirs are generally challenging due to the presence of many shale intercalations/laminations and/or due to increasing the shale volume represented in the form of dispersed distribution, and the dominance of conductive clay minerals. Therefore, in this study, the expected high resistivity values of the gas-bearing reservoir intervals of the Abu Madi Formation in the onshore Begonia gas Field, as a typical case study of the LRLC reservoirs, are masked due to the relatively high shale conductivity, particularly when the thickness of these intervals is less than the vertical resolution of the utilized conventional resistivity log. To verify the LRLC phenomena of the Begonia gas Field, the obtained data was compared to the South Abu El Naga gas Field as a normal case study with a relatively high resistivity gas-bearing pay zone. To overcome the impact of the conductive clay mineral content and identify these hidden low resistivity reservoir intervals, it is necessary to integrate the conventional logging data (gamma-ray, shallow and deep resistivity, density, and neutron) with the acoustic log data including shear and compressional sonic data. In this way, a useful relationship can be established enabling the detection of these hidden LRLC reservoir intervals. This integration is based on the principle that shear waves are not influenced by the fluids types, whereas the compressional sonic waves are influenced by the reservoir fluids. However, to effectively investigate these concealed LRLC reservoir intervals, which can boost production and increase the potential reserves, it is essential to have a low water cut value. The present study represents introduces an efficient workflow, which can be extended to other similar LRLC pay zones in the Nile Delta and northeast Africa. It is also extendible to the LRLC reservoirs in similar deltaic systems having conductive minerals-bearing reservoirs or thin beds.

Integrating machine learning and parametric design for energy-efficient building cladding systems in arid climates: Sport hall in Kerman

Climate change, driven by fossil fuel dependence, presents a significant challenge for the construction industry, particularly in energy-intensive regions like arid climates. This research investigates the potential of integrating machine learning and parametric optimization to enhance the energy efficiency of spatial structure domes in such environments. Focusing on a sports pavilion in Kerman, Iran, the study examines the crucial role of cladding systems in building energy performance. Employing a rigorous four-phase methodology, the research optimizes dome cladding materials for hot, dry climates using a dual objective function: energy cost and material cost. The process involves a comprehensive literature review, data-driven material selection, advanced energy simulations, and optimization analysis. Parametric modeling tools (Rhino, Grasshopper, Honeybee) facilitate the comparative analysis of various cladding systems. Multivariate Polynomial Regression (MPR) enables predictive modeling of energy consumption and material costs, streamlining the design process for architects. The optimized solution is a hybrid cladding model composed of 10 % polycarbonate and 90 % aluminum. Analysis reveals that the hybrid system offers superior energy optimization compared to pure aluminum (4.58 %) and polycarbonate (5.70 %). While polycarbonate has a lower initial material cost, the hybrid system achieves a balance between material expenditure and long-term energy efficiency. This highlights the importance of considering life-cycle costs when evaluating building envelope materials. This research advances a framework that leverages machine learning and parametric design for building envelope optimization. This framework empowers architects and engineers to create energy-efficient structures within arid environments, promoting a more sustainable built environment.

FDA Warning Letter Trends: A 15-Year Analysis

The U.S. Food and Drug Administration (FDA) plays a crucial role in safeguarding public health by regulating pharmaceutical and medical device industries. Warning letters issued by the FDA serve as a critical tool for enforcing regulatory compliance and highlighting significant violations that require prompt correction. Aim: The article analyzes trends in FDA warning letters issued to pharmaceutical companies from 2005 to 2021, identifying common violations, geographic distribution of recipients, and emerging regulatory concerns. The research is driven by the critical need to understand evolving FDA enforcement priorities and persistent industry challenges. Study Design: Retrospective analysis of publicly available FDA warning letters and related literature. Methodology: We reviewed 13 studies analyzing FDA warning letters, covering a total of 1,569 warning letters issued during the study period. Data were extracted on the frequency of warning letters, types of violations, geographic distribution of recipients, and emerging trends. Quantitative and qualitative analyses were performed to identify patterns and changes over time. Results: The annual number of warning letters increased significantly from an average of 17 in the early 2000s to 304 in 2020. Quality system issues were the most common violation, accounting for 34% of all citations from 2014-2016. Data integrity breaches emerged as a major concern, rising from negligible levels pre-2014 to 24% of violations by 2016. The proportion of warning letters issued to foreign manufacturers increased from 22.9% in 2019 to 33% in 2020. COVID-19 related violations accounted for 42.1% of all warning letters in 2020. Conclusion: FDA enforcement actions have intensified over the study period, with a shift towards systemic quality issues and data integrity concerns. The globalization of pharmaceutical manufacturing has led to increased scrutiny of foreign facilities. These trends highlight the need for robust quality management systems and proactive compliance strategies in the pharmaceutical industry. By synthesizing data from various periods and studies, this paper offers a longitudinal perspective on regulatory compliance issues to prioritize areas for improvement in quality management systems.

Recent Development in Detection and Control of Psychrotrophic Bacteria in Dairy Production: Ensuring Milk Quality.

Milk is an ideal environment for the growth of microorganisms, especially psychrotrophic bacteria, which can survive under cold conditions and produce heat-resistant enzymes. Psychrotrophic bacteria create the great problem of spoiling milk quality and safety. Several ways that milk might get contaminated by psychrotrophic bacteria include animal health, cowshed hygiene, water quality, feeding strategy, as well as milk collection, processing, etc. Maintaining the quality of raw milk is critically essential in dairy processing, and the dairy sector is still affected by the premature milk deterioration of market-processed products. This review focused on the recent detection and control strategies of psychrotrophic bacteria and emphasizes the significance of advanced sensing methods for early detection. It highlights the ongoing challenges in the dairy industry caused by these microorganisms and discusses future perspectives in enhancing milk quality through innovative rapid detection methods and stringent processing controls. This review advocates for a shift towards more sophisticated on-farm detection technologies and improved control practices to prevent spoilage and economic losses in the dairy sector.

Preparation and characterization of chitosan-rice starch films incorporating Amomum verum Blackw essential oil for grape preservation

The preservation of perishable food items presents a significant challenge in the food industry. In this study, we investigated the development and characterization of chitosan-starch films incorporated with A. verum essential oil for application in grape preservation. The films were prepared using a solvent casting method, and their physical and antibacterial properties were thoroughly evaluated. The films demonstrated tensile strength values ranging from 21.28 MPa to 27.64 MPa and elongation at break between 71.24% and 84.23%. The water vapor permeability values for chitosan-starch films were from 2.04 kg/Pa·s·m to 2.51 kg/Pa·s·m. In addition, the antibacterial activity of the films was assessed against Escherichia coli and Staphylococcus aureus. The results revealed notable inhibitory effects, with inhibition zones ranging from 14.41 mm to 21.00 mm. The films' efficacy in grape preservation was evaluated through storage experiments at room temperature for 9 days, comparing them with polypropylene film and unwrapped samples. The chitosan-starch films, particularly those containing 1.0% A. verum essential oil, exhibited superior performance in reducing weight loss and maintaining grape firmness compared to common packaging materials. Moreover, grapes covered with these current active bio-based films demonstrated higher antioxidant activity, indicating potential benefits for extending shelf life and preserving fruit quality. Chitosan-starch films incorporated with A. verum essential oil hold promise as effective and environmentally friendly packaging materials for grape preservation.

493 Predicting pellet quality using multiple linear regression with Principal Component Analysis (PCA)

Abstract Pellet quality is a crucial key performance indicator (KPI) for commercial feed manufacturing, which influences both the efficiency of the feed mill and downstream performance of animals fed these diets. However, due to the complexity of feed manufacturing and the large number of factors involved in the manufacturing process, controlling pellet quality is an ongoing challenge for the feed industry. Previous studies have mainly explored the impact of a few factors on pellet quality under experimental settings, and empirical equations have been seldomly developed to reflect the relationship between the factors and pellet quality under the commercial feed mill settings. This study aimed to establish a relationship between pellet quality and factors collected under the settings of a commercial feed mill. The data were collected from Trouw Nutrition Canada’s feed mill located in St. Marys, Ontario (Plant 2), between December 15, 2021, and December 6, 2022. During this period, 2,691 observations were collected, with each observation representing an individual batch of pelleted feed. A total of 75 factors were recorded, including 4 factors associated with the general information of each batch, 10 manufacturing parameters, 41 feed ingredients, 8 factors regarding the nutrient composition of each diet, and 12 environmental factors. Pellet Durability Index (PDI), which was the response variable, was determined for each batch using the Holmen method. The data were randomly split into an 80% subset for training and a 20% subset for testing. The training subset was used to construct the model via a 5-fold cross-validation, while the testing subset was withheld as an independent dataset to evaluate the generalization performance of the model. The response variable (PDI) was transformed (tPDI) using the Box-Cox method to meet a normal distribution assumption. To avoid multicollinearity, Principal Component Analysis (PCA) was used to reduce the dimensionality of the numeric factors before building the multiple linear regression model. The model prediction performance was evaluated on both the training subset (using 5-fold cross-validation) and the testing subset, and the prediction performance metrics were consistent between the two subsets (Mean Absolute Error = 1.94 ± 0.102 vs. 2.02; Root Mean Square Prediction Error = 2.47 ± 0.111 vs. 2.58; Mean Square Prediction Error = 6.12 ± 0.538 vs. 6.68; Concordance Correlation Coefficient = 0.538 ± 0.0231 vs. 0.490; Pearson Correlation Coefficient = 0.606 ± 0.0247 vs. 0.553, respectively). Most feed ingredients and nutrient compositions showed either positive or negative loadings on Component 1 (17.87% of total variance), and outdoor/indoor environmental factors were positively loaded on Component 2 (14.21% of total variance). The model developed in this study could help commercial feed mills better understand how various factors impact pellet quality and optimize the manufacturing processes of pelleted feeds.

Cold-Source Composite Welding Repair of 9Cr2Mo Thick-Walled Parts: Microstructure, Mechanical Properties, and Finite Element Simulation.

The restoration of large support rollers poses an industrial challenge due to the high energy consumption of traditional repair methods. Consequently, a novel approach for repairing support rollers has been introduced and tested on thick-walled components. Finite element simulations aided the study of welding repairs for large thick-walled components, examining element distribution, microstructure, mechanical properties, and residual stress distribution across various processes. The results indicate that employing ABAQUS2023 finite element software to analyze stress variations under different working conditions, the Dynamically Controlled Low-Stress No-Distortion method effectively mitigates residual stresses both during and post welding, reducing average transverse residual stresses by 14.5% and average longitudinal residual stresses in the weld zone by 29.1%. The Dynamically Controlled Low-Stress No-Distortion method narrows the high-temperature range of the heat source, consequently decreasing the size of the heat-affected zone by 33.3% compared to conventional welding. The microstructure featured dendrites and equiaxed columnar crystals, with the Dynamically Controlled Low-Stress No-Distortion method capable of grain refinement, transforming some equiaxed columnar crystals into cellular structures. As grains were refined, microhardness improved, with the covering layer's microhardness rising by 14.68%. A comparison between simulated and measured values of lateral and longitudinal residual stresses at corresponding points revealed discrepancies of 14.6% and 20.5% in accuracy, respectively.

Designing bipolar anodizing towards white anodic aluminum oxide (AAO)

Obtaining white anodic aluminum oxide (AAO) is a major challenge in the surface finishing industry. The present work presents a cost-effective route to design light-scattering morphologies through submicrometric hollows homogeneously dispersed in the depth of the oxide layer, created by localized hydrogen evolution. To this end, cathodic steps are added in alternance with anodic steps in a bipolar pulse anodizing process performed in 2 M sulfuric acid. The mechanisms of nucleation and growth of the targeted hollows within the AAO are highlighted by combining in situ electrochemical measurements and high magnification SEM observations. The aesthetic performances in terms of white color, evaluated by reflectance spectroscopy in comparison with a white reference, are directly related to the size, shape and distribution of the hollows, controlled by both the parameters of the cathodic step and the thickness of the unit anodic oxide layers.

Dynamic resource allocation and scheduling for appointment-based systems with walk-ins

Effectively managing constrained and perishable capacity amid fluctuating demands is a common challenge in service industries, often addressed through appointment-based systems that incorporate walk-ins. Balancing appointments and walk-ins is crucial for enhancing system value and maintaining stability. In this article, we study an integrated decision problem for appointment scheduling and resource allocation across multiple facilities, considering stochastic demands from three segments: priority customers, walk-in customers, and appointment customers. We formulate the problem as a sequential scheduling-allocation challenge using stochastic dynamic programming. Leveraging the anti-multimodularity of the value function, we fully characterize the optimal dynamic resource allocation policy and its monotone structural properties under any appointment schedule. Given the complexity and intractability of optimal scheduling with dynamic resource allocation, we introduce two suboptimal scheduling policies—vertical scheduling and horizontal scheduling—and a heuristic allocation policy. Additionally, we create an Upper Bound (UB) for the original problem as a surrogate, establishing an asymptotically optimal UB for the scaled problem through its objective value and a corresponding lower bound through its solution. This UB solution serves as an efficient and effective heuristic, demonstrating superior performance compared with the combined performance of suboptimal scheduling policies with optimal dynamic resource allocation, especially as problem size increases. It also holds significant practical implications for integrated pooling systems.

Navigating Challenges in the Palm Oil Industry: Sime Darby Plantation’s Strategic Response to the COVID-19 Pandemic

This paper explores the impact of the COVID- 19 pandemic on Sime Darby Plantation Berhad (SDP), the world's largest producer of certified sustainable palm oil (CSPO). With a significant reliance on foreign labor, SDP faced substantial challenges due to border closures and movement restrictions imposed during the pandemic. The analysis focuses on the labor shortage, decreased production, and fluctuating global demand for palm oil. It also examines the measures SDP implemented to mitigate these challenges, including enhanced safety protocols, recruitment of local workers, and efforts to reduce dependency on manual labor through increased automation and mechanization. The evaluation of these strategies highlights their short-term effectiveness and potential long-term sustainability. The paper concludes by emphasizing the importance of technological innovation in overcoming labor shortages and ensuring SDP's continued growth and leadership in the palm oil industry.

Meeting the Industrial Challenges of CO2 Photocatalytic Reduction: Moving From Molybdenum Disulfides to Oxysulfides Based Materials?

Reducing CO2 emissions is one of the greatest challenges of the century. Among the means employed to tackle CO2 emissions, the photocatalytic conversion of CO2 is an appealing way to valorize CO2 since it uses the sun energy, which is abundant. However, nowadays, the best photocatalytic systems still report too low efficiencies, and use expensive materials, so they cannot be readily industrialized for use at large scale. In this report, we first highlight general industrial and process challenges (including operating conditions). Then, focusing on MoS2/TiO2 heterojunction systems, we analyze advantages and limitations of such systems and open perspectives on Mo oxysulfides supported on TiO2 discussing their potential to reach higher efficiency for CO2 photoconversion.

Enhancing Flight Delay Predictions Using Network Centrality Measures

Accurately predicting flight delays remains a significant challenge in the aviation industry due to the complexity and interconnectivity of its operations. The traditional prediction methods often rely on meteorological conditions, such as temperature, humidity, and dew point, as well as flight-specific data like departure and arrival times. However, these predictors frequently fail to capture the nuanced dynamics that lead to delays. This paper introduces network centrality measures as novel predictors to enhance the binary classification of flight arrival delays. Additionally, it emphasizes the use of tree-based ensemble models, specifically random forest, gradient boosting, and CatBoost, which are recognized for their superior ability to model complex relationships compared to single classifiers. Empirical testing shows that incorporating centrality measures improves the models’ average performance, with random forest being the most effective, achieving an accuracy rate of 86.2%, surpassing the baseline by 1.7%.

Recovery of bioactive compounds from oil palm waste using green extraction techniques and its applications

SummaryOil palm (Elaeis guineensis) is a major oil crop that significantly contributes to the Indonesia's and Malaysia's economic growth. However, oil palm processing for oil extraction generates substantial waste, such as palm kernel cake, palm‐pressed fibre, oil palm empty fruit bunches and palm oil mill effluent, which pose noticeable environmental challenges. This review explores green extraction techniques for palm waste processing, which include microwave‐assisted extraction, deep eutectic solvents, ultrasound‐assisted extraction, supercritical fluid extraction, enzyme‐assisted extraction and subcritical water extraction. The potential for industry scaling, mechanisms, applications and challenges of each technique used for oil palm waste are discussed. Microwave‐assisted extraction, ultrasound‐assisted extraction and supercritical fluid extraction are particularly promising for large‐scale production, while deep eutectic solvents paired with ultrasound‐assisted extraction show the potential to improve extraction efficiency. This review also reveals that green extraction techniques are sustainable alternative to conventional techniques by effectively recovering valuable compounds from waste with reduced environmental impact. Additionally, the diverse applications of bioactive compounds (vitamin E, phytosterols, phenolics, polyphenols and flavonoids) extracted from oil palm waste in food, pharmaceutical, cosmetic and other industries are also presented. Valuable components such as cellulose, dietary fibres and bioactive peptides derived from the waste can be applied in food coatings, high‐protein products and drug delivery systems. Biosorbents, biofuels and biodegradable products derived from the waste would also provide environmental benefits. Future research should focus on optimising the green extraction techniques for industrial use to promote responsible production and circular waste management to foster health and environmental safety.

Biodegradable and antioxidant films with barrier properties to visible and ultraviolet light using Hass avocado (Persea americana Mill.) by-products

The search for renewable sources that can be used to develop products as alternatives to traditional polymers in the future, without affecting food safety, represents a challenge for the food industry. In this context, agro-industrial waste has emerged as an interesting alternative. This study evaluated biodegradable films made from Hass avocado seed flour without (Control film; PC) and with antioxidant extracts (PExBIO and PExIND) derived from the epicarp of the same fruit. The results showed that all the films blocked visible (over 96 %) and ultraviolet light (99.9 %), which was mainly attributed to perseorangine, a compound generated by the action of polyphenol-oxidase. The films also exhibited good water vapor barrier properties. PExIND showed the highest mechanical strength (Young's modulus = 901.8 ± 33.4 MPa; tensile strength = 9.1 ± 1.0 MPa; elongation = 3.5 ± 0.5 %), correlating with the highest crystallinity index (14.9 %). The incorporation of extracts increased the content of phenolic compounds and antioxidant capacity in PExBIO and PExIND compared to PC, with no significant differences between them. Moreover, the biodegradation test indicated that the films showed high biodegradability. Therefore, Hass avocado residues could be used to produce biodegradable antioxidant films, suitable for packaging light-sensitive and low-moisture products.

User-Centered Design in the Face of Limited User Access

Time with users is a precious commodity that has become increasingly difficult to come by, making it difficult to always employ traditional user study methods. Such methods also run into challenges in sensitive industries, where it is not always possible to openly engage with end-users. These barriers jeopardize good design, and limited user access seeds temptation to bypass user engagement altogether. The primary goal of this work is to share techniques and lessons learned for successful user engagement in the face of limited access to end-users. Three methods are presented here, usage of subject matter experts (SMEs), analogous use cases, and surrogate users, along with key successes and challenges for each. The lessons, limitations, and suggestions presented here reflect work performed across multiple projects over the past several years, where we have utilized combinations of these techniques for conducting user-centered design in the absence of regular direct user engagement.