Logo
Contact Us
Case studies
Case study
Case study

MES Manufacturing Execution System at Brintons Agnella

Digital Transformation project delivered for a luxury rug brand factory.

Shifts
3/24
Employees
~550
Processes analyzed
12






1. About Brintons Agnella

Agnella is an luxury rug brand. Behind the unassuming facade of its factory, lies a rich history that stretches back to 1975 - making Agnella one of the most established manufacturers in Europe. Their rugs and carpets can be found in high-end establishments world-wide: from Western Europe, all the way across oceans to Australia and the USA.

GGS was invited to collaborate on a Digital Transformation project. Base on a market analysis in the manufacturing sector we learned that the benefits of such projects include:

b6b2932e366fc78e465e9ebf47a83d4b_MES_benefits.png

2. Discovery

The discovery phase for this project was split into two parts:

  • business process mapping
  • determining Agnella's business goals



4f35df7b52e8c577616614045abba335_IMG_3554.jpg

The first stage of the analysis included a series of meetings with Agnella's staff responsible for the manufacturing process. The company's management played a key role in navigating the course of the project. Overall, the following people were involved in the discovery stage:

  • Production staff;
  • Team leaders;
  • Shift managers;
  • Administration staff;
  • Department managers;
  • IT department.

2b4f3e80635c74f93a96b84def958b07_MES_process.png

This phase included a series of meetings with senior management, after which we presented our findings. It was crucial that we understood production priorities, both from the engineering and IT perspective.

We reached the point at which we needed to consolidate our ideas and decide on how to execute them. Our options were:

  • Build a complex product that will achive the senior managers' business goals - long term
  • Develop the product in modules - each delivering a valuable, reliable, stand-alone MVP - mid term

The final consultations with Agnella's senior management brought us to the conclusion that time would be a constraint, their expectations were high, our resources were limited. We decided to build a Manufacturing Execution System, with the goal of combining operational data:

  • Related to manufacturing departments;
  • Punch-in and punch-out times;
  • Payroll;
  • ERP.

We perceived that such information would address the company's cost optimization needs and bring value to the company.

fcfd4113e7ae5dff757f89d3712c05e6_mpv-illustration.png

The following conclusions became evident at this stage:

  • The project was going to be complex and challenging.
  • We would have to prove our solution's value in a short time frame.
  • BPMN and business process mapping would be crucial.
  • A minimum amount of documentation supports the development of a high quality Digital Transformation project.

3.Development

Effective planning of our works seemed like an ambitious task made not any easier by the numerous obstacles we were facing:

  • Time - the main obstacle that can make or break any project.
  • Development team - consisting of 3-4 people + a Scrum Master and a Project Manager. It couldn't be any larger due to budget limitations.
  • Scope - the MVP had to bring in value from the start.
  • Covid - the factory where the project was to be carried out was located in Białystok, while the Project Team resided in Cracow.

The implementation was segmented to include:

  • Development (in User Stories and Features)
  • Testing
  • UAT(user acceptance testing)
  • Dry Run (only 1 shift in the factory)
  • Go Live (rollout covering the entire factory)

We were also aware that the nature of Digital Transformation projects, where changing needs are a common occurrence, called for evangelists within the organisation. Support from a line manager was instrumental in the implementation of the solution.

8e143c07a8866b0f5bbf16d74bb4df43_main.jpg

The GGSITC team works flexibly and precisely, delivering the project successfully in spite of all obstacles. The project, tailor-made to fit the specific needs of our spinning mill, more than lived up to my expectations - the app is easy-to-use and the large amounts of data it gathers are something we had previously struggled to process.

Leszek Karpiński, Manager

Conclusions:

  • Deep dive and understanding of the solution by the company's employees is crucial to its successful implementation; it saves both parties a lot of time.
  • Oracle and MySQL databases can cooperate - at GGS, we're dedicated to proving that.
  • Even hundreds of gigabytes of data can be processed and decyphered within a limited time.

4. Transformation: from MVP to Flywheel

We consider this the most demanding stage of this digital transformation project. We had to oversee many moving parts simultaneously:

  • Support of the newly-launched app.
  • Development of new functionalities, often asked after by employees.
  • Optimisation of the existing product. We're not perfect - mistakes are unavoidable, but we want to address them swiftly to avoid the creation of technical debt.
  • Search of new evangelists who'll convince the unconvinced.

This process is ongoing and based on the lean manufacturing methodology, which helps in optimizing the Total Manufacturing Cost.

Conclusions:

  • Weekly sprint planning with product owners (line managers, HR managers) is one of the key factors impacting the successful execution of the project!
  • If you gather and share insightful data with the right people, you'll always find affordable cost-wise, value-building areas to optimise.

b3d1155b426fda31602d99414c5917f8_report.jpg

5. General conclusions:

We crated the system of checks and balances that ensures the information is accurate. By combining Business Process Automation tools with the willingness to improve the company's bottom line, numerous improvements to the manufacturing process were introduced. The project also proved that Manufacturing Execution System:

  • drives labour efficiency 🚀
  • drives OEE overall equipment effectiveness 📊
  • drives capacity planning 📈
  • drives capacity optimization 📉
  • reduces hiring costs (because you need fewer people) 💰
  • identifies efficiency problems 🏭
  • identifies equipment problems very quickly 🛠️
  • helps with manpower requirements 👷‍♀️👷‍♂️
  • enables tracking of costs per machine / employee hour ⏳