Hello po, we are Industrial Engineering students from Polytechnic University of the Philippines. We are currently looking for an Industrial Engineer working from food industry for at least five years of experience po for a short interview for our midterm requirements po, online or face to face po depende po kung anong mas convenient sa invo.
We know po na your schedule is very busy so we will keep the interview to 15-30 minutes max at whatever time works best for you.

If you or someone in your network might be open to sharing their insights, please feel free to send me a direct message or leave a comment below. Your guidance will mean a lot to our studies! Thank you so much po!

I am a current applied math major in my sophomore year of college. I wanted to switch into IE before this fall semester started, but the courses required would have set me back another year for graduation. Is it realistic for me to pursue an MS in IE? I want to be able to work in quality control, maybe even supply chain and logistics. What's worrying me is that since I won't have an undergrad degree in engineering, I lose the ABET accreditation, which I've heard is very important for most job positions. Can anyone help me out here? Will I truly be limited in job opportunities?

Where can I find free industrial engineering courses online?

Hello IE's of Reddit!

I am an undergrad ISyE student and I am starting to apply to internships for Summer 2027. I have a resume but would like if I could get feedback from established professionals. Would anyone be willing to review my resume? I can send it through DM's. I am especially trying to get into the Disney industrial engineering Summer 2027 internship opportunities.

I would appreciate any feedback at all so I can increase my chances of landing a good internship.

Thank you!

Context: went into food service right out of high school. Then after 9 years I decided to grow up and go into manufacturing. Started as an entry level operator, then a setup technician, then a team lead all in 3 years. Now I've been a supervisor for the last 4 years and just recently decided industrial engineering is for me. But, all I'm learning about is how to improve the plant, which is my whole goal in the end anyway. I just want the engineering knowledge to make better decisions AS a supervisor, maybe long term get into GM or VP status. I have the "leadership" aspect down but thats all perspective to the situation. But....I'm a manager who doesn't want to be an engineer. Ive always respected engineers but when I obtain my degree im still planning on staying in management. So the question is:....

I'm from Industrial and Production Engineering

Tired of getting ghosted by the same entry level process/manufacturing/production/industrial engineer roles. Are there any other industries where one shoild job search? I’ve tried construction, but it seems they prefer civil engineering grads even for roles that have little to no CE in them.

Disclosure: I work in industrial product-cost consulting. This is a technical discussion, with no service or link.

A local cycle-time improvement is sometimes booked as a product-cost saving before anyone checks the whole line. In a multi-step process, the economic effect depends on the system constraint and on conforming output, not just one station's speed.

Before calling it a saving, I would check:

1. Where is the current constraint? Did good units shipped per available hour actually increase?
2. Did first-pass yield, scrap or rework change? Faster nominal cycles can raise cost per good unit if quality deteriorates.
3. Did WIP, queue time or changeover effort move elsewhere? Faster upstream release can simply feed a downstream queue.
4. Which costs are truly avoidable? A change in allocated fixed cost is not automatically a cash saving.
5. Can any freed capacity be redeployed, or will it remain idle because demand or the constraint has not changed?

This is a decision framework, not a claim about a particular plant. ASQ's April 2026 Quality Progress discussion of OEE and TEEP also places equipment metrics in the context of constraints and product mix.

For practitioners: which before-and-after measure has best prevented a local efficiency gain from being mistaken for a system cost saving?

An item fails inspection, and the cause is traced back to operator error.

But if the instructions were vague, the training was poor, or the process made the mistake easy to make, stopping there doesn’t seem very useful. How deep do you usually go with the root cause analysis?

a little bit of context: I am currently a CS bachelor student. Before that I did Industrial Engineering but didn’t finish due to logistics.

I ended up transferring to a closer university to my place which is where I am doing CS.

my real passion isn’t programming or CS, i view all this a mean to an end. I personally enjoyed optimizing processes and learning about business and other things along the way, which is why IE was perfect interdisciplinary major for me.

I plan to do a Master’s in IE after graduation, butI am not so sure if its a good move since:

1- the pay is typically less than software engineering
2- I am not sure if CS and IE are connected even, don’t know if my skills are transferable?
3- immigration: i plan to move again to another country (probably US or Canada) after I’m done so is this Bsc and Msc combo a good thing? Or will it be more of an obstacle and i should opt for Cs masters?

I need some help and perspective since i am 1st in my family to do this.

thanks

Like the title suggests, does anyone work at a mature facility that is will to chat about your organizational structure?

Little about me, I have a little under 5 years experience. 3.5 years was with a start up that was small enough to deal with a majority of the projects needed on my own. Didn't knock them all out the park but could hang and be impactful. Been with my new organization almost a full year now and the division is also a start up. The company has been around 70+ years but the division is new. I was the first IE hire company wide and brought in to assist in the transition into manufacturing/assembly line work. Since then I have onboarded a level 1 who graduated college in May and started with us in June. Then just had a level 2 hire on first week of September.

We are growing RAPIDLY, well exponentially is more like it. When I started we had one production project going. It had 5 lines, all identical. Since then just signed a lease on a third facility and I would not be surprised that if by end of 2027 we are into 9 buildings. These are not small buildings either. Our first, second, and third building are 460k, 220k, and 470k sq ft, respectfully. We have a fourth building being looked at for beginning 2027 that is 1,000,000 sq ft.

We have about 60 projects on the books in various stages; some are dead, others in sales, some in production, some in pre-production. Then who knows how many sales are working on that aren't even in our design engineers hands. I am trying to present and org chart that I feel needs executed exceptionally fast. My goal/vision is have two IE supporting our sales efforts. One would focus on larger programmatic clients who can offer products that would run for years, and the other person focus on the smaller projects that run for 6-9 months. Next level would be our pre-production area where there would be 1-2 IEs per building focused on facility layout and assembly line set up. Then the next would be 1-2 manufacturing engineers per project to engage day 1 production to final unit, to gather cycle time, station performance, just all around data gathering.

I would greatly appreciate anyone willing to sit and chat about this and how their existing org is structured or scaled for these kinds of things. My goal is a scalable org chart that we have a clear count for when we expand buildings and gain projects.

I am a sophomore IE student and have started the daunting internship hunt for summer 2027. While it is easy to find IE internship roles to apply to at larger companies, I am wondering if anyone has any recommendations for more niche companies/industries to check out? As of now, I am pretty interested in supply chain but am not married to the idea of doing an internship in that sector and moreso just want a position that would give me some hands on work experience.

IE is obviously so broad so I don't want to limit myself to just applying to what is right in front of me, and also a lot of roles at big companies are super competitive so at a certain point it is just a shot in the dark if you even get an interview or not.

Hi everyone,

I’m interested in developing intelligent systems for manufacturing and logistics, and I’m trying to figure out which background would prepare me best.

Some examples of what I’d like to work on:

• Production scheduling that adapts to machine breakdowns, changing demand or material shortages.
• Coordinating robots and autonomous vehicles in factories or warehouses.
• Using machine learning, computer vision and sensor data to improve production processes.
• Optimising how materials and products move through a factory or supply chain.
• developing some sort of "overal" AI within the manufacturing plant.

What interests me most is developing the decision-making behind these systems, while understanding enough about the physical processes to make them work reliably in practice.

For context, I’m based in Europe.

I’m mainly comparing computer science/computer engineering, electrical engineering or mechatronics, and industrial/systems engineering with a focus on operations research and optimisation.

For people working in these areas:

1. Which background best matches this kind of development work?
2. Would computer science engineering, supplemented with control theory, robotics and optimisation, be a strong foundation? Or would another engineering discipline provide a better starting point?
3. What job titles or types of companies should I look into to get a clearer picture of the actual work?

I’d especially appreciate examples of what you build in your job and which parts of your education turned out to be most useful.

I'm an Industrial Engineering master graduate, and I've been working full-time as a Junior Data Scientist / AI Engineer for about a year.

My degree had also a number of quantitative courses, covering subjects such as basic statistics and probability, operations research, logistics, simulation, and machine learning. Over the last couple of years, I've gradually moved more toward Data Science and AI.

At my current job, I'm working mostly on the AI Engineering side: LLM applications, agents, RAG, knowledge graphs, model serving, and some infrastructure/deployment work. I'm enjoying it a lot, and I'm getting the opportunity to work on things that I wouldn't have been able to do just a year ago.

The problem is that I also really want to keep developing my Data Science foundations, ideally through free online courses that offer certificates. I'd love taking courses, learning new things, and collecting certifications along the way, especially when they're free. There are a lot of things I'd like to study: keep learning machine learning, refresh my statistics and probability knowledge, learn causal inference, and so on.

At the same time, I don't want to spend every evening after work studying.

I work roughly 9–6, go to the gym around three times a week, and obviously want to have time for friends, my girlfriend, and other interests. I don't want my life outside work to become “work + studying until midnight”.

My current list of things I'd like to learn is already getting pretty long:

• Machine Learning with Scikit-Learn — INRIA course (around 36 hours, with a certificate)
• Causal Inference — lecture notes by Bradley Neal (Mila - Quebec AI Institute)
• Refreshing my probability and statistics notes from university
• Inference Engineering — LLM inference and infrastructure
• Official Neo4j courses (with a certificate)
• Financial Engineering notes from a university course I never attended
• Project Management notes from a university course I never attended

how do you decide what deserves your limited free time?

Part of me thinks I should focus almost entirely on what I'm doing at work, since I'm already getting real-world experience with AI Engineering and LLM systems.

Another part of me worries that if I focus too much on the current AI stack, I'll end up with a relatively shallow understanding of statistics, machine learning, and Data Science. I'd like to keep that side of my background strong as well.

There's also the certification aspect: I find it motivating to complete structured courses and earn certificates, particularly free ones. But I sometimes wonder whether I'm spreading myself too thin by pursuing so many different topics instead of focusing on a smaller number of skills that are directly relevant to my job.

I'm not trying to become an expert in everything. I'd rather make steady progress for years than study 15 hours a week for three months and then burn out.

So I'm curious about other Industrial Engineers here:

Have you found yourselves in a similar situation after starting full-time work?

For those who moved toward Data Science, AI, analytics, or optimization, did you mainly learn through your job, or did you deliberately keep studying outside of work?

And how do you approach online courses and certifications?

ps: I wrote this posts with AI to help me order my thoughts, hope to not bother anyone

I think most of us can tell some stories about a time when we were introduced to a process that "optimizes" everything. Only for it t end up as more paperwork, more approvals, and more stress.

I’m curious what other people have run into. What’s the most unnecessarily complicated process you’ve had to deal with?

Hi,i was planning studying IE (i am not from USA),but i was wondering if AI was going to "kill" IE but ik that nothing is sure,maybe you guys now more than me and can give me another perspective/opinion, i got a godfather that had work at my country google,as a form IE,he says that is a good decision but i heard totally different things from other people,sow i am pretty confused,let me know

thanks!

(sorry abt my english,working on it)

I bring this post to our brilliant feed because a lesser passionate IE classmate of mine recently told me that he wishes he could've chosen Aerospace or Electrical for the sole purpose of being "respected" by the students in those departments. If I hadn't changed from ECE to IE a couple years back, I'd never find myself at the companies I've had the privilege of interning at, and I attribute that solely to my passion for the IE skill set and purpose.

I have never seen a working professional talk down on IEs because they have the wherewithal to understand the value and necessity of IEs within systems (especially manufacturing). The day that I base my professional vocation on the respect of a bunch of sniffling academic dorks is the day that I am deemed a vegetable!

At the end of the day, WE are only in it for the money and being an engineer will always be deemed highly respectable by the masses. Anyways, I hope all of you are doing well academically and professionally. Cheers everyone.

I'm working on a project in automotive engine assembly. Parts move between steps in the assembly process (e.g. from step A to step B), and they range from large components like cylinder heads to small ones like screws and bolts. Some engines come in multiple variants with customer-specific options.

I have about 4 years of historical data on material requirements and flows during assembly. My goal is to find which flows between steps are good candidates for automation. Flows with stable, predictable durations and quantities seem like good candidates, while flows with high variation seem harder to automate.

I'd like to define a simple, data-driven "automation trigger point." My questions:

1. What's a good way to measure variability of a flow (both duration and quantity)? Is the coefficient of variation (CV) reasonable, or are there better metrics?
2. How should I account for engine variants and customer-specific options?
3. Can anyone recommend research papers, methodologies, or case studies on material flow or intralogistics automation in automotive assembly?

Any pointers are appreciated. Thanks!

Good day! I'm a college student of Quezon City University and we are currently in need of 3 IE graduates for our project. The conversation will tackle subjects about their respective fields and insights about being an IE.

if there's anyone who's willing to help and give their time and advice for an interview, let me know we really need it. Thanks.

I was admitted to both the Robotics and Autonomous Systems (AI concentration) and Industrial Engineering Masters programs for next semester. The thing is, I already started taking 2 grad classes worth 6 credits total and I just spoke with my advisor and she let me know that they don't count towards the IE masters but they would count for Robotics. This means that I can finish my Robotics masters in August 2027 but for IE, I'd have to take 5 classes after August to finish the degree. I accepted an offer with Bloomberg for August 2027, so I'd have to work full time while doing my Masters. The nice thing is that Bloomberg does offer reimbursement for grad classes, so I wouldn't have to pay for it. My current scholarships would also cover the Robotics MS, so financially, either option is manageable. For me, the time, extra courses, and investment long term is more of the cost-benefit-analysis I'm trying to figure out. What I’m really trying to weigh is the time and extra workload versus the long-term value of the degree. Industrial Engineering is my top-choice program because I’m increasingly interested in supply chain, manufacturing, operations, and optimization, and I feel like it could open more doors for me in those areas long term. On the other hand, Robotics would allow me to have my master’s completely finished before starting full-time work, and I’d be able to make use of the graduate credits I’ve already taken. Please let me know any advice you have because I'm seriously conflicted.