Bending Metal: Improving Sheet Metal Repair at Tobyhanna Army Depot through Lean Six Sigma

The Army's Lean Six Sigma methodology includes five phases: Define, Measure, Analyze, Improve, and Control (DMAIC); each of these phases includes interaction between the stakeholder and process team. This paper focuses on the application of Lean Six Sigma methodology at Tobyhanna Army Depot to help reduce overruns and repair cycle time within the sheet metal cost center. At the initiation of the project, the process incurred over 4,000 hours of overruns, a situation in which it takes longer to repair an asset than the standard hours allocated for the repair. Additionally, the average repair cycle time, amount of time required to repair an individual asset, exceeded customer expectations by almost four days. The paper describes recommended solutions to address both problems.

Six-sigma and quality planning of TORCH tests in the Peruvian population: a single-center cross-sectional study

Objective To ensure the health of newborns, it is necessary to perform high-quality diagnostic tests. The TORCH panel is a set of tests that identifies infectious pathogens such as Toxoplasma (Toxo) and Cytomegalovirus (CMV) that are common in low-setting populations. We performed TORCH panel quality planning using six sigma in a reference laboratory at Peru. Results This was a cross-sectional study. TORCH tests include Toxo, Rubella, CMV, and Herpes. We processed all samples by fourth-generation ELISA on the GEMINI XCR200 analyzer (Diatron, Budapest, Hungary). We obtained the imprecision from the annual data of the external quality assessment plan and we used the CLSI EP12-A3 guideline. In a total of 44,788 analyses, the average imprecision was 3.69 ± 1.47%, and CMV had lower imprecision (2.3 and 2.6% for IgM and IgG, respectively). Quality planning of the TORCH panel allowed estimating the sigma value that ranged from 4 to 10 (average 7 ± 2 sigma), where rubella had the highest values (10 for IgM and 8 for IgG) while HSV2 had the lowest values (4 for IgM and 5 for IgG). Our results suggest the optimal performance of half of the markers including Toxoplasma, Rubella, and CMV in the Peruvian population.

Six Sigma in Human Resources

HR business partner, Business Excellence are some buzzwords in the industry nowadays. Profitability and efficiency are being driven through various strategic initiatives aligned to the vision of the organization. Customer satisfaction is now being replaced by customer delight. Organizations are taking steps ahead of voice of customer. The consumer insights are thoroughly analyzed and interpreted. Data analytics is not restricted to only finance and operation functions but are widely used across the support functions along with line functions. Human resource is now considered as an asset. Organizations are also trying to find out ways to capitalize the full potential of human asset. Various tools and methodologies are paving its way to bring efficient human resource management practices. Six Sigma is one of the tools, which is booming into the application space of Human Resource Management. Six Sigma is being considered as a business process and is helping the in shaping and improving their bottom line by designing and monitoring various activities to reduce the defects.

Quality control challenges post covid-19 crisis: an integrated IoT and IoP approach

The Covid -19 is arguably the biggest pandemic in history and there are a lot of challenges that must be dealt with. One of the biggest challenges post Covid-19 is to tackle quality control challenges. This research paper discusses some of these challenges and solutions using an integrated internet of things (IoT) and internet of protocols (IoP) based approach and further showing its implementation in the industry world and hence, proving to be a solution for damage assessment. With the help of IoT- enabled quality control system, six-sigma rule is also analysed. Post Covid crisis, it is important for every institution to gain back customer trust so quality of materials should be maintained and IoT enables us to do the same. The unification of industrial IoT (IIoT) and industry 4.0 is also discussed as it leads us to understand that this unification is the next evolution of smart manufacturing and digital technologies. This methodology can lead us to accelerated innovation in applications for overcoming the eventual challenges post Covid in the near future. Also, small-scale/large-scale companies making use of the above research methodology can adhere to six-sigma criterion.

Reliability Analysis and Optimization for the Brake Drum

In order to research the static and dynamic characteristics of drum brake in the braking process and avoid resonance, it is necessary to carry out static analysis and modal analysis of drum brake. By establishing the three-dimensional model of the brake drum and imported to ANSYS for static analysis, the maximum equivalent stress and maximum deformation of the brake drum are obtained. The first, second and third natural frequencies and modal vibration shapes of the brake drum are obtained by modal analysis. Four dimensional parameters are selected as design variables, and the sensitivity is carried out by using experimental design. Taking the maximum deformation, first natural frequency, second natural frequency and mass of the brake drum as the objective function, the multi-objective optimization algorithm is used to optimize the design variables. Based on the optimization design, the six sigma reliability analysis of the brake drum is carried out, and the six sigma reliability analysis method is given in detail. The cumulative distribution graph of the maximum deformation, first natural frequency, second natural frequency and mass of the brake drum are obtained. The analysis results show that the reliability of the brake drum is close to 100%, and then it is judged that the brake drum has high reliability. The research results provide a reference basis for structural reliability analysis.

Applicability of Six Sigma in Human Resource Management

The role of HR has become like that of a firefighter, remembered only in emergencies. Their presence is felt only in their absence. HR is seen as a reactive staff function and a cost centre. The message is clear. Despite its best effort to keep organization together with uniform policy, norms, and values, HR is compelled to prove its financial worth to the organization. HR is under constant pressure for showing their results in quantifiable and financially measurable terms. Introducing Six Sigma in processes of HRM functions seems to be a solution to this problem. However, in some of “Total Six Sigma Organizations,” the human resources department has been practically untouched by Six Sigma. The main reason being the difficulty in quantifying and measuring the financial returns of HR processes. But, some others feel that this is as easy as identifying the gaps and using the right formula. The real problem therefore lies in the perception of an individual HR professional. It takes an HR manager to think statistically and analyze how a process can be quantified.