Production schedule for a automotive motor head manufacturing plant Anirudh Jagannathan aj2560 Jorge Ortiz jeo2130 Yanira Pichardo yp2323

Problem description  The plant we will be studying is Nemak’s Plant #4 in their Monterrey site, focusing on their core blowing operation.  A consultancy project took place back in 2010, with one of the deliverables being an Excel workbook with macros that automated the creation of each week’s production schedule.  The production schedule workbook delivered back then was done in such a way as to try and meet the production deadlines as much and as well as possible( Ʃ L max ) and try and make each machine finish around the same time, having the minimum amount of downtime as possible ( Ʃ C max ).

Process diagram Milling Core blowing Motor head molding Cleaning De- burring Packaging for shipping SandResinAluminum Core assembly Destroyed cores Excess aluminum Motor head

Project objective  We want to determine the following: 1.Was the production schedule proposed back in 2010 optimal or not ( Ʃ C max, Ʃ L max ) 2.How we could improve it. 3.How far from optimal was it.  Stretch goal 1.Figure out if the way the Excel macro was programmed (running time) was efficient or not, going into Big O notation.

Problem complexity 1.The plant has 21 core blower machines. 2.Production requirements for the following week arrive each Thursday morning and are detailed on a daily basis (daily due dates). 3.Plant managers can set priorities to each product that is in the production requirements for the week. (weights for each job) 4.Each core blower can blow certain types of cores for each product. 5.Each core blower can work with only a certain set of toolings. 6.Each product is made up of multiple cores and there are cores that form part of more than one type of product. 7.We have information regarding core blower machines and tooling availabilities for each week (sometimes either machines or tooling are undergoing preventive or corrective maintenance). 8.We have information regarding the current state of the inventory and in some cases, for some products, there is a “produce up to level”.

Scope delimitation  The Excel workbook is complex and has many functionalities, however for this project we will only focus on the following: Functionalities Product requirement by day (due dates) Prioritization of product requirements Machines’ available hours Tooling-Machine compatibility Tooling availability Setup times Scrap percentages OEE (Overall Equipment Effectiveness) Cores (Build of materials for each product) Initial inventory Detailed production schedule Summarized production schedule Daily schedule by machine graph Machines’ hours in use for the week graph Unallocated remaining production hours Functionalities Milling capacity Sand requirements (raw materials) SAP / historical data Carts (to transport the finished cores) Milling used capacity graph Unallocated remaining production hours  The following functionalities were dropped from our analysis:

General macro logic 1.Daily turntable requirements 2.Product prioritization 3.Machine availability 4.Tooling availability 5.Initial inventory (automatically pulled by the macro) 6.Build of materials for each product 1.Sort the products using the prioritization list. 2.Consult the product’s build of materials. 3.Consult the initial inventory. 4.Determine if the core being analyzed is in stock or it has to be produced. 5.If the product has to be produced, allocate an available tooling. 6.Allocate to the first available machine that is compatible with this tooling. 7.Go to the next core of that product until you finish its build of materials. 8.Go to the next product down the prioritization list until you finish with the whole requirements list, or you run out of available machine-hours in the day. 1.Detailed production schedule 2.Summarized production schedule 3.Graphs INPUTS PROCESS OUTPUTS

Current scheduling

 By using the wrap-around rule there’s risk that if a machine breakdown occurs (specially late during the day), you might be unable to fulfill your orders because you are missing one or more of the cores required to assemble a specific product. J 2 J 3 J 2 t=Dt=0 J 1 M1 M2 M3

Proposed scheduling  By using an alternative scheduling algorithm, where a job is assigned to each machine and once all machines have a job assigned to them you assign a second job and so on, you can reduce the aforementioned risk, reduce the makespan, and balance your operations (little or no idle time in machines). J 2 J 3 t=Dt=0 J 1 M1 M2 M3 t’=D’

Proposed scheduling

Proposed scheduling algorithm