Crushing the lack of differentiation: An AHP-based inventory classification for Sandvik Rock Processing

Abstract

Problem Statement: Sandvik Rock Processing is in the need for a classification tool, which can help them improve their inventory management. Currently, there are problems with inefficiencies with deficit as well as excess in inventory. The new classification shall the basis for the differentiation of service levels and facilitate a shared view on items’ importance.

Purpose: The purpose of this thesis is to develop and propose a framework for classification of Sandvik Rock Processing’s stone crusher components, which can be used to improve their inventory management.

Research Objectives: The first objective is to describe SRP’s current inventory management of stone crusher components. The second objective is to identify and rank the criteria against which an item should be assessed to determine its importance in SRP’s inventory management. The third and final objective is to develop a framework for item categorization that can be used to improve SRP’s inventory management.

Method: The thesis was conducted using the design science research methodology. Initially, a literature review was conducted to gather relevant background knowledge. Thereafter, data was gathered through interviews with SRP staff, as well as from the company’s ERP system. Analysis of the data served as input to the artefact development process, which aimed to create the above-mentioned inventory classification tool.

Conclusion: As a foundation for the following steps, an overview of SRP’s existing inventory management approach was first established. Then, five criteria were identified as important when assessing items and ranked in the following order: criticality, forecasted demand, actual usage, price, and lead-time. Lastly, an inventory classification model was developed as the artefact in the design science approach. This used the analytical hierarchy process as a classification technique. The classification tool was developed iteratively to gradually reach a more suitable classification.

Popular Abstract

A Swedish company had over 22,000 component parts in stock – but no way to know which ones were truly critical. Our thesis introduces a tool to identify the parts that matter most, helping avoid costly downtime.

Having the right component at the right time can be the difference between smooth operations and costly breakdowns. But when your inventory includes tens of thousands of items, how do you know which ones are truly critical? In our master’s thesis, we developed a practical classification tool to help companies prioritize their inventory – and back it up with data.
We worked with Sandvik Rock Processing (SRP), a Swedish industrial company that produces large-scale rock crushers. At their production unit in Svedala, over 22,000 components are stored as inventory. Yet, all items were treated more or less equally when it came to availability targets – regardless of how vital they were to operations. This “one size fits all” approach led to both unnecessary stock and costly shortages. To address this, we designed a classification framework using the Analytic Hierarchy Process (AHP), a method that helps decision-makers weigh several criteria simultaneously.
Through interviews and data analysis, we identified five key factors: criticality, forecasted demand, actual usage, price, and lead time. We then created a scoring model that combines these into a single value, allowing SRP to sort its inventory based on what actually matters most.
One surprising finding was how skewed the inventory value distribution was: a tiny share of components accounted for most of the value and usage. Meanwhile, the majority of items took up space and tied up capital, without contributing much to the operational value. The model we built is intentionally simple to use and easy to adapt. It can be implemented using standard tools like Excel and integrated into existing inventory workflows. The goal isn’t to overcomplicate – but to give companies like SRP a smarter basis for making stocking decisions, especially when every minute of downtime comes with a hefty pricetag.

• author: Marklund, Arvid and Lindgård, Nils
• supervisor: Sandeep Jagtap
• organization: Production Management; Engineering Logistics
• alternative title: Krossa avsaknaden av differentiering: En AHP-baserad artikelklassificering för Sandvik Rock processing
• course: MTTM05 20251
• year: 2025
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Inventory Classification, Inventory Categorization, ABC analysis, Inventory Management, Analytical Hierarchy Process, Stone Crushers
• other publication id: 6039
• language: English
• id: 9193004
• date added to LUP: 2025-06-17 17:08:09
• date last changed: 2025-06-17 17:08:09