Sundar, P.S.; Chowdhury, C.; Kamarthi, S. Industrial Internet of Things Enabled Kata Methodology of Assembly Line Productivity Improvement: Insights from a Case Study. Processes 2024, 12, 2611. https://doi.org/10.3390/pr12112611
https://www.mdpi.com/2227-9717/12/11/2611
HVAC Assembly Line
Case Study 88
Ajay Kumar
• 1st1st
Robotics | Warehouse automation (Conveyors, Sortations, AS/RS, Picking, Dock)
24 August 2025
A leading FMCG & Grocery company has a challenge:- demand was growing faster than their shipping process could keep up.
🚚 Trucks were waiting too long at the docks.
📦 Workers manually sorted cartons and pushed trolleys to the right vehicle.
⏳ Dispatching even a single wave of orders took hours.
The warehouse was running at full capacity, but speed to shelf was slowing down.
That’s when automation stepped in.
✅ Conveyor sortation systems now automatically direct cartons to the right dock, no manual guesswork.
✅ Automatic truck loading takes it a step further - products roll straight into the vehicle in the right sequence, stable and ready for the road.
The results?
Dispatch times cut dramatically.
Labor effort reduced, safety improved.
Orders hit the retail shelves faster, keeping stores stocked and customers happy.
Today, the warehouse runs like clockwork -- goods flowing in, sorted with precision, and shipped out in record time.
Bastian Solutions, designed thre solutio for this bottleneck.
Smart Warehouse - ECommerce
Bastiam partner with Toyota Logistics
Watch the video
Bastian’s India team and Toyota Material Handling India Pvt Ltd teamed up under the
Toyota Industries Corporation umbrella to showcase powerful, integrated automation solutions!
At a recent tech conclave focused on India’s agricultural value chain, we shared how digital innovations in ASRS pallet handling, case handling and material handling can drive big results—no matter the project size.
https://www.linkedin.com/company/bastian-solutions/posts/?feedView=all
Here are a few technologies transforming the warehouse processes.
🔹 Tilt-tray Sorters: Trays that tilt at just the right moment to drop parcels into their correct chute. Perfect for high-speed, high-volume operations.
🔹 Cross-belt Sorters: Small belts ride on a main track, shifting parcels sideways with pinpoint accuracy. Ideal for handling a mix of shapes and sizes.
🔹 Shoe Sorters: Sliding “shoes” gently guide packages off the main conveyor. Fast, reliable, and kind to fragile items.
🔹 Robotic Arm Sorters: AI-powered and built for complexity. These flexible arms can scan, pick, and place with precision that rivals human dexterity.
Why do I care so much about sortation?
Because I’ve seen firsthand how even a 1% improvement in accuracy can have a ripple effect—less rework, better inventory control, faster deliveries, and a smoother experience for both teams and customers.
In logistics, it’s often the smallest efficiencies that lead to the biggest gains.
Taylor rubric: "an increase in productivity was allocated (1) one-third to the worker in the form of increased wages, (2) one-third to the owners in the form of stock dividends and capital investment, and (3) one-third to consumers in the form of lower prices for the products the company produced."
Interesting. What’s in a Name? The Trials and Tribulations of IIE!
Bill Biles, Professor of IE, Retired at University of Louisville
https://www.linkedin.com/pulse/whats-name-trials-tribulations-iie-william-e-biles-phd-bill-biles/
Case Study.123
https://lineview.com/en/solutions/lineview/
https://lineview.com/en/case-studies/coca-cola-casestudy/
20% performance
improvement at
Coca-Cola Enterprises
The Challenge
With manufacturing sites across Europe, it was no surprise to learn that Coca-Cola Enterprises (CCE, now CCEP) had many different systems being employed to manage plant performance and were achieving mixed results.
SOLUTION
CCE introduces LineView™ sitewide to instantly and accurately identify the critical area of focus
CCE chose the LineView system as the standard production line monitoring system for their Supply Chain Division. Over three years, LineView has been implemented on every European production line to help increase efficiency and reduce manufacturing costs.
The visual user interface presents actionable information in an easy-to-read format, enabling rapid decision-making and allowing production teams to focus on taking effective action rather than analyzing and interpreting the data.
LineView
Key Benefits:
• Data and AI driven targeted actionable insights
• Seamless integration into existing ERP and MES solutions.
• Automated true causal loss and production monitoring
6-Loss Analysis
Applying 6-Loss Analysis and Theory of Constraints principles, LineView identifies the effect of all downtime on the overall line output without any operator intervention and accurately pinpoints the true cause of productivity loss.
Rigour & Routine for Data Use
To meet the new challenges of the business as they arise and achieve ever-higher levels of performance, Lineview defined the rigor and routines around data use that have driven ongoing, sustainable performance improvement.
Once LineView was installed, the accuracy and availability of information and the potential for real improvement made a giant leap forward. The system has been implemented on more than 70 production lines across Coca-Cola Enterprises.
Site-wide increase in OEE of 20% within 24 months
OEE or Overall Equipment Effectiveness represents the percentage of manufacturing time that is 100% productive. A 1% improvement would itself translate to millions in additional revenue. Coca-Cola Enterprises plants improved their OEE by 20% less than 24 months of LineView™ implementation.
Improvement of 6% across the entire enterprise
Individual sites achieved an impressive 20% increase in OEE, while operations across the wider enterprise achieved a combined 6% improvement in production and distribution. The benefits of LineView™ extend beyond the production halls. We call this the ripple effect of efficiency improvement.
ROI delivered on logistics savings alone
An effective and efficient investment delivers the highest return on investment (ROI) for any business. Lineview delivered ROI for Coca-Cola Enterprises through significant savings in logistics costs. This improvement was driven by an overall increase in yield and consistent quality, leading to a more efficient supply chain and cost savings.
“The power of LineView is in the speed with which teams can identify the real losses to efficiency whilst providing the drill-down necessary for highly effective problem solving.”
Richard Davies
Vice-President Operations,
Coca-Cola Enterprises Ltd.
20%
OEE increase site-wide in 24 months
6%
Improvement across entire enterprise
$$
ROI delivered based on logistics alone
More case studies available on LineView site.
ud. 25.8.2025
Pub. 18.2.2025
I developed an online education/training session on "Effective Industrial Engineering and Productivity Management." I can present the session in one hour, one and half hour or two-hour long sessions. The sessions will be valuable when company industrial engineers and other engineers and managers attend as a group. Industrial engineers require active cooperation and participation of other engineers and managers in their studies and projects. Hence a common presentation and discussion on effectiveness will be very useful.
Supporting Information.
Effective Industrial Engineering - Some Thoughts by Narayana Rao K.V.S.S.
Effective industrial engineering has to satisfy management about the contribution it made to the organization year after year.
The prime contribution of IE has to be cost reduction through productivity improvement.
https://nraoiekc.blogspot.com/2025/07/effective-industrial-engineering-some.html
IE Cases and Information
Information - 87
Please go through
2002
https://heuft.com/en/actual-news/news-overview/news-archive/inspection-systems-in-the-filling-plant
Bottle Cap Inspection based on Machine Vision.
2016
INTRODUCTION
In 2011 the international electrical and electronics approved the feature extraction for fill level and cap inspection in bottling machine which described the automated visual inspection system (AVIS) for cap closure and over/under filling [1].
Inspection of bottles crates in the beer industry through computer vision described about region of interest and segmentation of the crates. Even though the bottles orientation present in the crates may change, this method identifies the odd one [2].
A real-time machine vision system for bottle finish inspection described the real time inspection which involves selection of camera, selection of light settings, software selection and discussed about inspection algorithm [3].
Development of a Computerized Method to Inspect Empty Glass Bottle described that examined in this paper.
1. L. Yazdi, A. Prabuwono, and E. Golkar, "Feature extraction algorithm for fill level and cap inspection in bottling machine," in Pattern Analysis and Intelligent Robotics (ICPAIR), 2011 International Conference on, 2011, pp. 47-52.
2. M. Campos, M. Ferreira, T. Martins, and C. Santos, "Inspection of bottles crates in the beer industry through computer vision," in ECON 2010 – 36th Annual Conference on IEEE Industrial Electronics Society, 2010, pp. 1138-1143.
3. Feng, W. Yaonan, and L. Huanjun, "A real-time machine vision system for bottle finish inspection," in Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th, 2004, pp. 842-846 Vol. 2.
https://www.ijert.org/bottle-cap-inspection-based-on-machine-vision?amp=1
