Since its foundation, Lean practices have played crucial role in reduction of wastes in a given process to maximize efficiency. Adoption of Lean practices in several industries have opened wide scope to study its impact on many fields such as agricultural sector. Post-harvest stage within agricultural supply chain is known to have gaps in terms of assuring good storage practices. The losses at post-harvest level have significantly impacted the availability of sufficient food for global population. These losses occur due to lack of compliances with good management practices. The literature of this study identifies shortfalls in the management practices of the grain storage containers in United States. The grain elevators are most common technology in use which assures the security of the raw food grains after harvest stage and right before its transfer to next stage. Adoption of good management practices by grain elevators thus becomes crucial to secure the safety of the nutritional quality of the grains which is vital to ensure food security and keep food losses low.<div><br></div><div>The thesis considers the shortfalls associated with the management practices of grain elevators and propose to adopt Lean as a solution. The outcomes of this research present a descriptive analysis of the lean readiness survey completed by the superintendents of the grain elevators in corn belt region of United States (primarily in Illinois and Indiana). The lean readiness results reveal the extent to which the elevators are ready to adopt lean practices.The research also identifies the readiness level which indicates highest as well as lowest level of readiness levels towards lean adoption. The conclusion presents the summary of final outcomes of lean readiness level based on the surveyed elevator superintendents.<br></div>

<p>Lean Six Sigma (LSS) has been implemented worldwide for many years and has been successful in many organizations. Eloot, Huang, and Lehnich (2013) noted that achieving manufacturing excellence by using LSS was an opportunity for many companies. Liker and Rother (2011) pointed out that only 2% of companies successfully achieved the desired results with Lean plans. </p> <p>The presented dissertation identified the critical success factors of LSS implementation for Chinese manufacturing companies and explored the challenges occurring during the LSS transformations. The objectives of this dissertation were: </p> <p> i. to understand how the employee training process for LSS can be designed using total quality management (TQM) adoption in private manufacturing organizations in China;</p> <p> ii. to understand how LSS practices can be adopted successfully in SMEs in China;</p> <p> iii. to examine and explore the critical success factors (CSF) of LSS implementation;</p> <p> iv. to discuss the challenges occurring during LSS transformation.</p> <p> </p> <p>Objective (i) was achieved through a descriptive single case study. This case study showed how to apply <a>a design for Six Sigma methodology (DMADV) for staff training in quality management tools in a private organization in China</a>. The author also discussed the problems occurring during the Six Sigma project and explored how organizational culture impacted Six Sigma implementation. Objective (ii) was achieved through a detailed descriptive single case study which recorded how LSS practices were adopted successfully in a SME-VTCL in China using DMAIC methodology. Survey data was collected to identify and explore the critical success factors of LSS implementation in SMEs, by querying the voice of top, middle, and frontline management, as well as frontline workers of these companies. Objectives (iii) and (iv) were realized utilizing descriptive, exploratory, and multi-case studies designed to gather and analyze observational and interview data. The resulting interview data, and the key factors for successful LSS transformation of these three companies were discussed from the perspective of senior management and LSS promoters within the companies. Based on interview data and the Lean iceberg model, a new LSS transformation model was proposed. The author also developed 6 propositions based on the findings from the interviews. </p> <p>In summary, the results of this study provided value and references for LSS practitioners to expand the body of knowledge on the strategies used to implement LSS successfully inside organizations. The findings of this research may potentially lead more Chinese organizations to successfully adopt LSS to provide customers with high-quality products. The three LSS implementation cases described <a>critical success factors (CSFs)</a> and challenges that occurred during the transformation, may improve the success rate of implementation, help enterprises achieve the desired results through LSS, and enhance the sustainability of LSS implementations.</p>

With the growing popularity of using smartphones in business environments, it is increasingly likely that phones will be the target of attacks and sources of evidence in cyber forensic investigations. It will often be important to identify who was using the phone at the time an incident occurred. This can be very difficult as phones are easily misplaced, borrowed, or stolen. Previous research has attempted to find ways to identify computer users based on behavioral analysis. Current research into user profiling requires highly invasive examinations of potentially sensitive user data that the user might not be comfortable with people inspecting or could be against company policy to store. This study developed user profiles based on changes in a mobile phone's underlying block structure. By examining where and when changes occur, a user profile can be developed that is comparable to more traditional intrusion detection models, but without the need to use invasive data sets. These profiles can then be used to determine user masquerading efforts or detect when a compromise has occurred. This study included 35 participants that used Samsung Galaxy S3s for three months. The results of the study show that this method has a high accuracy of classifying a phone's actual sessions correctly when using 2-class models. Results from the 1-class models were not as accurate, but the Sigmoid SVM was able to correctly classify actual user sessions from attack sessions. <br>

<div> <div> <div> <p>Approximately 60% of lean manufacturing systems result in failure (Pearce & Pons, 2019). The failures are attributed to a lack of understanding of lean principles and a lack of commitment by employees (Almanei, Salonitis, & Tsinopoulos, 2018). The study hypothesized that incorporating augmented reality (AR) into the processes, would improve the overall success rate. An AR proof of concept was conducted using the Toshiba dynaEdge AR100 (Dynabook, 2019). The question that guided the proof of concept was, “how did instructional task times compare between AR instruction’s and paper instruction’s?” The literature review provided findings that the incorporation of AR contributing to a 33% decrease in fabrication cycle times (Segovia et al., 2015). The literature review also provided findings that AR incorporation worked best for complex assembly tasks (Capozzi, Lorizzo, Modoni, & Sacco, 2014). The study utilized 20 subjects, which were split evenly into two groups for each set of instructions. The 20 individuals were timed, and the data was analyzed using a two-sample t-test and a Cohen’s d effect size analysis. The AR system’s perceived usability was also analyzed through the use of a system usability scale (SUS). The study’s findings for the t-test and the effect size analysis did not support the previously stated hypothesis. However, the AR system was determined to be useful, based off of the SUS findings. The study provides future researchers a starting point for AR related studies and an understanding of what to avoid. </p> </div> </div> </div>

The term “IoT” has evolved to encompass a wide range of diffuse concepts, but the common thread among the myriad definitions has been the convergence of technology to bring <i>advanced conveniences</i> to our every day, but complicated, lives. A long-term focus of the Collaborative Robotics Lab, and a particular focus of many with interests in consumer assistance, has been the kitchen, which acts as the “nerve center” of the home in many cultures. However, despite the grand vision of revolutionizing the kitchen and improving our lifestyles with technology, what today’s IoT-integrated appliances and kitchen-focused conveniences offer is mainly limited to a remote control. While remote control is certainly convenient, it still requires human planning in both cognitive and physical loads in performing cooking activities. The goal of this thesis is to build a framework of the network of IoT-enabled kitchen appliances, <i>TupperwareEarth</i> for the “Internet of Kitchen Things” integrated with an inference engine that utilizes ontology as a knowledge database. From simple clustering of sensor data to recommender systems that employ crowd-sourced preference data, the cognitive burden is reduced with proactive suggestions to high-level queries based upon the current kitchen state. Through the progression of the studies in the “Internet of Kitchen Things,” <i>TupperwareEarth </i>aims to reduce human planning that involves both cognitive and physical loads of burden by inferring solutions to the activities of daily kitchen living using ontological semantics.

Abstract: The purpose of this research was to understand: (1) the influence that an industry-situated STEM lab experience has on students’ (ages 10-18) perceptions of careers in manufacturing, and (2) the challenges and opportunities that this space presents. To answer these questions, this study analyzed participant pre- and post-draw a manufacturer tests as well as manufacturing career perception surveys that included Likert-scale items and open response questions. Along with these data sources, five semi-structured interviews were conducted with industry stakeholders in order to understand the conception and operation of the STEM lab, as well identify any challenges or opportunities to improve or replicate success for other industries. From there, the data were analyzed through thematic coding for the drawings, open-response questions, and interviews, and a Mann-Whitney U test was performed on the survey results in order to look for general shifts in responses to specific questions from before to after the STEM lab experience. The results gained from the three different data collection techniques were looked at in aggregate and used to triangulate specific understandings, questions, and recommendations. The results confirmed a lack of students’ awareness and understanding of manufacturing, misperceptions surrounding the careers within, and a disconnect between industry needs and educational output. Along with the data, literature on vocational psychology supports the need for students to participate in authentic learning opportunities to build self-efficacy and form more accurate outcome expectations with regards to future career selection. However, the data did reveal that the industry-situated STEM lab experience likely led the participants to an improved understanding of the manufacturing ecosystem and provided an opportunity for local educators to engage with industry. While this research looked at a novel application of a STEM lab and highlighted its influence on students’ perceptions of manufacturing careers, there is obviously no “silver bullet” for fixing the talent pipeline for manufacturing and continuous work in this area needs to be done.

<p>Black women’s underrepresentation in STEM disciplines remains an urgent problem of major concern in higher education institutions across the United States. The purpose of this investigation was to explore Black women’s experiences in an active learning STEM Human Centered Design course at a Predominantly White Institution. It also examined how these experiences influenced Black women’s intent to persist in STEM educational pathways. Black Feminist Thought Theoretical Framework was used to conceptualize and interpret the experiences of five Black female first year undergraduate students at a Predominantly White Institution in the Midwestern region of the United States. This qualitative case study research utilized semi structured interviews, direct observations, and documents to gather and triangulate data for this study. The findings from this study revealed that: (a) <i>Imposter Syndrome: An Enduring Internalized Question of Competency, </i>(b) <i>Undermining of Academic Abilities</i>: <i>Cross Examination of Intellect,</i> (c) <i>Lack of Diversity: A Colorless Norm,</i> (d) <i>Isolation: Intrinsic Sensitivity of Separation from Others</i> were the salient experiences facing these five undergraduate Black women. This investigation contributes to the dearth of scholarship on Black women in STEM by highlighting their undergraduate experiences in a STEM course, and describing ways to ensure their persistence towards STEM educational pathways.</p>

This study examined the relationships between graduate student gender, advisor-advisee gender match, advisor selection methods, graduate student satisfaction with advising, overall satisfaction with graduate/professional programs, health and well-being. Graduate Student Experience in the Research University (GradSERU) public-use data collected from Purdue University and the administrative records of the 2019 Purdue University Graduate School were used in the study. A series of simple linear regression analysis in the Statistical Package for the Social Sciences (SPSS), version 26.0 and RStudio version 3.6.2, were used for all data analysis. Male graduate students reported significantly higher health and well-being scores than their female counterparts. The relationship between advisor-advisee gender match, satisfaction with advising, and overall satisfaction were found non-significant in this particular sample. Advisor selection method was a significant factor in graduate student satisfaction, health, and well-being. Implications, limitations, and recommendations for future research are discussed.

The pursuit to combat climate change continues, identifying new methods and technologies for sustainable energy management. Automakers continue developing battery electric vehicles while researchers identify new applications and materials for solar photovoltaics. The continued advancement of technology creates new holes within literature, requiring investigation to understand the unknown. Photovoltaic vehicle integration gained popularity during the 1970s but did not commercialize due to technology, economics, and other factors. By 2021 the idea resurfaced, showcasing commercial and concept vehicles utilizing photovoltaics. The emergence of new transparent photovoltaics presents additional options for vehicle integration but lacks literature analyzing the energy output and economics. The theoretical analysis investigated transparent photovoltaic replacing a vehicle’s windows. The investigation found that transparent photovoltaic vehicle integration generates energy and financial savings. However, due to high system costs and location, the system does not provide a financial payback period like other photovoltaic arrays. Improving cost, location, and other financial parameters create more favorable circumstances for the photovoltaic system. Furthermore, transparent photovoltaics provide energy saving benefits and some return on investment compared to regular glass windows.

<p>In the current manufacturing industry, static work instructions (WI) are still widely used for manufacturing assembly training and they lack the dynamic information that interactive work instructions can offer. Augmented Reality (AR) training systems are receiving increasing interest in the scientific community, but there is a limited amount of research done on the long-term effect of the AR training systems compared with static training systems. This thesis study was done to investigate if interactive WIs such as AR WIs and 3D PDF WIs have an advantage on training efficiency and knowledge sustainability compared to static paper WIs. Within an experiment, it was observed that there are no differences between the three training methods when it comes to training efficiency, but AR WI proved to be more effective in sustaining the user’s long-term recall precision than paper WI.</p>