Manufacturing Time & Motion Study Intern

AKSHAY NARAYANAN

****, ******* *****, ******** ******, Apt.S-206, Dearborn, Michigan-48126.

313-***-**** addrhv@r.postjobfree.com https://www.linkedin.com/in/akshay-narayanan-688620b0 Summary:

• Graduate Industrial Engineer with background in Six Sigma, Continuous Improvement, Production and Operations, Total Quality Management, Product development and seeking Full Time Opportunities in the same field

• 1-year internship/ training in Manufacturing, Continuous Improvement, Operations, Quality control and Process improvement.

• 1-year hands-on experience in projects involving product development, capability analysis and Lean Six sigma techniques. Tools: Skills:

Design Tools: AutoCAD Kanban, KANO model, APQP, SAP QM, Ishikawa Diagram DVP&R, Statistical Tools: Minitab, Microsoft Office Excel Demand forecasting techniques, Root cause analysis, SPC, Oracle ERP, Computer Literacy: Python, C++, Microsoft Office suite. Material Management tool: Oracle ERP, Microsoft Dynamics

(Navision)

FMEA, 5S, Kaizen, Regression modeling.

Educational Qualification:

University of Michigan-Dearborn Graduated On: April 2020 Master’s in industrial And Systems Engineering GPA 3.97/4.0 Amrita Vishwa Vidyapeetham, Coimbatore, India Graduated On: August 2017 Bachelor’s in mechanical engineering GPA 7.46/10

Experience:

Manufacturing Time & Motion Study Intern, Peckham, Inc. September 2019-Present

• Responsible for performing Predetermined Motion Time Studies (PDMTS) to evaluate the efficiency of apparel sewers and determining the hourly rate of production.

• Introduced a Rank order cluster matrix for part machine mating to facilitate better machine layout and increase production efficiency. This yielded a decrease in labor hour costs from $30,000 to $26,700 for the production line.

• Produced a Rack and tote system using Visio to implement a Kanban card pull system with a goal of reducing Work in Process Inventory.

• Performed Process mapping of the wet weather suit line to eliminate NVAs and increased the efficiency by 32%. The NVAs were identified as unwanted hand-ironing taking place in the line.

• Conducted a time study of entire line of wet weather and insulation garments and generated a spreadsheet comparing current process stance Vs. target turn-around time by visually representing gaps using bar charts.

• Generated Stack charts to present findings on possible areas of waste elimination by studying different movements in the shop-floor.

• Updated Standardized work charts with updated process steps, after eliminating unwanted wastes in the form of motions and wait time.

• Accelerating a PFMEA kaizen for faulty red and yellow tag fabric rolls, with the intention of assigning RPNs to various failure modes and probable causes with the goal of facilitating pre-emptive supplier identification.

• Involved in a problem-solving Kaizen to resolve mixed marker issue in the spread cut area and implemented 5S to color code and match labels (garment cut tickets) with one garment at a time.

• Currently running a line balancing project to better use Level 4 & 5 apparel sewers and to identify bottlenecks against targets by conducting a capacity study.

Manufacturing Engineering Intern, Forbes Marshall Pvt Ltd; May 2019-June 2019

• Worked with the Quality Control/Assurance department in raising Non-conformity reports and filing CAPA with the supplier to make sure the next batch of castings for piston valve assembly are defect free and as per dimensional tolerance.

• Actively used SAP QM to create inspection plans for the production line of pressure gauges.

• Achieved a reduction of Turnaround time from 75 minutes to 54 minutes on a project to conduct mapping of an assembly process of the boiler plate to cut down on time by identifying the Non-value add actions.

• Performed a KANO model study to translate the KPI(key performance indicators) from customer requirements to product functionality on a piston valve housing assembly. Also created DFMEAs for flange castings to identify and prioritize failure modes to resolve. Engineering Intern, Mettur Thermal Power Plant: May 2015

• Worked on the mapping process of various stages involving electricity generation such as steam generation and running turbines to understand the process flow and find out problem areas.

• Applied Root cause analysis to find the various causes of the problem involving steam generation.

• Monitored and verified air fuel ratio inputs using Control charts. Engineering Intern, Steel Authority of India Ltd (SAIL): June 2014

• Worked on monitoring the process parameters in the manufacture of carbon steel slabs with emphasis on heat treatment temperature and compression.

• Performed a value stream mapping on the entire process of cold roll steel manufacture to identify areas of potential improvement under the oversight of the Industrial Engineer.

• Applied statistical process control techniques in the final manufacture of the cold rolled steels. Academic projects:

New product development- Automated Stovetop cleaner: September 2019-December 2019

• Working on implementation of various techniques and steps of a new product development starting from scratch.

• Identified 3 products via brainstorming and decided upon the development of one among those by researching the patenting possibilities.

• Proposed the problem definition and the need statement for the product and identified the customer base from which we derived the customer requirements.

• Identified customer requirements and prioritized them by using KANO model and KANO questionnaire and by conducting a customer research survey.

• Created a KJ affinity diagram to group the various customer requirements under five functional groups to further systemize them.

• Created a Functional family tree diagram to identify the primary and supporting functions of the products. The final output of the functional family tree converts the customer requirements into functional requirements of the products using a verb-noun model technique.

• Generated a list of metrics to quantify the functional requirements and ensured all customer requirements are met at least by one metric.

• Created a QFD chart representing the competitive and marginal benchmarking done by comparing three different vacuum cleaning products on the market to set marginal and ideal values for the various metrics.

• Created a customer need- metric matrix to represent the mapping of the needs to the metrics and see if the design is axiomatic in nature.

• Performing patent searches to generate ideas and create concepts for developing a working model of the product.

• Using SCAMPER methodology to brainstorm the possibilities of the modifying and improving the product ideas and design implementation.

• Using Pugh analysis to generate a weightage matrix to evaluate various possible concepts and prioritize the development process.

• Creating a DFMEA table to determine the Severity, Occurrence and Detection rating of various modes of failure possibilities and rank them by Risk priority number (RPN) for further Poka-Yoke analysis of that particular failure mode. Analyzed the inventory management and supply chain principles of COSTCO: December 2018

• Performed forecasting for operational profit, revenue, income for the ensuing five year period using a time series model.

• Inventory control and supply chain techniques were analyzed to know process optimization techniques. Assessed and improved process capability of manufacturing of projector lamps: November 2018-Decmber 2018

• By measuring current performance of process and determining the performance gap in process capability, the necessary improvements were implemented and kept in control using NP attribute charts. Analysis of manufacture of 3D printed components: January 2017- May 2017

• Worked as lead on a quality improvement project “Optimization of Process Parameters Of 3D Printing for Better Mechanical Properties” to achieve optimum printing parameters.

• Listed several factors affecting the various mechanical properties of the test component for further Statistical testing.

• Developed models by analyzing data using Taguchi’s DOE techniques and carried out Statistical tests using Minitab and Excel.

• Performed ANOVA analysis to evaluate significant factors and optimized the mechanical properties. Improved the compressive strength from 23.106 (N/mm2

) to 27.0629 (N/mm2

).

Certifications:

Certified Lean Six Sigma Green Belt: January 2019

• Trained in implementation of lean tools such as 5S, Poka- yoke, Kaizen as well as performing FMEAs, MSA, Capability analysis. MIT’s EdX certification program: January2018 – March 2018

• Obtained a certification in Supply chain fundamentals focusing on demand forecasting, Inventory and Transportation management, warehousing and various aspects of logistics in an organization.

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