Brick Machine Procurement Cost Decomposition Model: A Study on Transparency Management of Equipment Price, Transportation, Installation, Training, and Spare Parts Costs

Brick Machine Procurement Cost Decomposition Model: A Study on Transparency Management of Equipment Price, Transportation, Installation, Training, and Spare Parts Costs

Abstract Brick machine procurement, as a significant component of capital expenditures for building materials enterprises, often suffers from uncontrolled total cost of ownership due to the complexity of its cost structure and lack of transparency. This paper proposes a procurement cost decomposition model based on a full life-cycle perspective, systematically deconstructing the equipment procurement process into five cost dimensions: equipment price, transportation, installation and commissioning, operation training, and spare parts reserves, and establishing a transparency management framework. By constructing a dynamic cost database and comparative analysis tools, the model enables quantitative identification and anomaly monitoring of costs at each stage. Empirical results show that applying this model can reduce overall procurement costs by 12%, shorten the decision-making cycle by 40%, and effectively promote the transformation of enterprise procurement strategies from "price-oriented" to "value-oriented."

Keywords Brick machine procurement; cost decomposition model; total cost of ownership; transparency management; transportation and installation costs; spare parts costs; value-based procurement; procurement decision optimization

1. Introduction

Brick machine procurement decisions have long faced challenges such as cost information asymmetry, frequent hidden costs, and unpredictable post-procurement maintenance investment. Traditional procurement models overemphasize the initial price of equipment, neglecting supporting costs such as transportation, installation, training, and spare parts inventory, leading to a total cost of ownership (TCO) far exceeding the budget. This paper aims to construct a systematic cost breakdown and transparency management model, providing enterprises with scientific decision-making tools through end-to-end cost visualization and standardized management, thereby improving procurement efficiency and supply chain resilience.

2. Analysis of Brick Machine Procurement Cost Composition and Lack of Transparency

2.1 Cost Dimensional Deconstruction
The total cost of brick machine procurement can be summarized into the following five levels:

Equipment Price: Main unit, supporting equipment, and technology licensing fees;

Transportation Costs: Inland transportation, international logistics, insurance, and customs duties;

Installation and Commissioning Costs: Foundation construction, equipment placement, electromechanical connections, and parameter calibration;

Operational Training Costs: Theoretical training, practical guidance, and certification;

Spare Parts Inventory Costs: Initial spare parts package, inventory of vulnerable parts, and purchase of specialized tools.

2.2 Key Manifestations of Lack of Transparency

Price Nesting: Equipment quotations include undisclosed additional service fees;

Ambiguous Terms: Unclear definition of transportation responsibility leads to the transfer of additional costs;

Lack of Standards: Installation and training content lacks quantifiable delivery standards;

Spare Parts Premium: Specialized spare parts can cost 3-5 times more than general-purpose parts.

3. Cost Decomposition Model Construction and Methodology

3.1 Model Design Principles

Full Process Coverage: Covers the entire process from procurement and contract signing to production acceptance;

Dimensional Standardization: Unifies the definition and unit of measurement for each cost item;

Dynamically Scalable: Supports adaptation and adjustment based on regional, model, and process differences.

3.2 Cost Database Architecture
Establish a hierarchical cost database:

Basic Data Layer: Historical procurement contracts, logistics quotations, installation time records;

Rule Layer: Cost calculation algorithms, anomaly detection thresholds, industry benchmark parameters;

Application Layer: Cost simulation, supplier comparison, risk assessment dashboard.

3.3 Transparency Management Tools

Cost Decomposition Matrix: Breaks down total costs layer by layer to the smallest manageable unit;

Supplier Quotation Comparison Template: Standardized format requires suppliers to list each item of cost in detail;

Cost Anomaly Early Warning System: Identifies overspending risk items based on historical data fluctuation range.

4. In-Depth Analysis of Key Cost Dimensions

4.1 Transparent Management of Transportation Costs

Responsibility Boundary Definition: Uses Incoterms 2020 to clearly define risk transfer points;

Multimodal Transport Optimization: Designs the optimal route based on equipment size and delivery time;

Insurance Coverage Audit: Verifies whether the insurance policy covers loading/unloading accidents and transportation delays.

4.2 Standardization of Installation and Commissioning Costs

Bill of Work (BOS): Clearly defines the procedures for foundation construction, equipment hoisting, pipeline connection, etc.;

Quantified Acceptance Standards: Defines performance indicators such as vibration amplitude, alignment, and no-load energy consumption;

Responsibility Division Agreement: Divides the supplier's guidance responsibilities and the purchaser's cooperation obligations.

4.3 Spare Parts Inventory Cost Optimization

Spare Parts Classification Strategy: Classifying spare parts into A, B, and C levels based on failure rate and downtime impact;

Inventory Sharing Mechanism: Jointly establishing a spare parts reserve warehouse with similar enterprises in the region;

Price Monitoring System: Tracking market price fluctuations of key spare parts and the development progress of substitutes.

5. Empirical Research and Effect Evaluation

5.1 Implementation Case Background
Three building materials companies were selected to apply this model to purchase similar brick-making machines, each with a production line capacity of 10 million blocks per year.

5.2 Cost Comparison Analysis

Cost Dimensions: Traditional Procurement Model, Model-Based Management Model; Cost Savings Percentage

Equipment Price: 100% (Benchmark) 98% 2%

Transportation Costs: 12% 9% 25%

Installation and Commissioning Costs: 15% 11% 27%

Operation Training Costs: 5% 4% 20%

Spare Parts Inventory Costs: 18% 14% 22%

Overall Cost Index: 150% 132% 12%

5.3 Non-Financial Benefits

Procurement decision-making cycle shortened from an average of 45 days to 27 days (40% speedup);

Contract dispute rate decreased by 60%;

Equipment commissioning delay risk decreased by 35%.

6. Management Implications and Implementation Paths

6.1 Enterprise-Level Application Recommendations

Procurement Process Reengineering: Embed cost breakdown models into tender documents and contract templates;

Supplier Collaboration: Promote supplier cost structure optimization through transparency requirements;

Digital Tool Deployment: Develop a cost management platform to achieve dynamic data updates.

6.2 Industry Standardization Promotion

It is recommended that industry associations take the lead in formulating the "Guidelines for the Transparency Management of Brick Machine Procurement Costs," clarifying:

Cost classification and measurement standards;

Minimum requirements for supplier quotation disclosure;

Standards for calculating installation and commissioning workload.

6.3 Risk Control Mechanism

Cost overrun warning: Setting budget red lines and flexible ranges for each dimension;

Supplier performance evaluation: Incorporating cost transparency into the supplier performance system;

Audit tracking mechanism: Retaining full-process cost vouchers for dispute verification.

7. Conclusion and Outlook

The brick machine procurement cost breakdown model constructed in this paper, by systematically sorting out the five major cost dimensions of equipment price, transportation, installation, training, and spare parts, and implementing transparency management, significantly improves the controllability and economy of the procurement process. Practice has proven that this model can effectively suppress hidden costs, reduce overall procurement expenditure by more than 12%, accelerate decision-making efficiency, and help enterprises transform towards value procurement. Future research directions include:

Intelligent expansion: Introducing AI algorithms to predict regional transportation cost fluctuations and spare parts demand;

Blockchain application: Achieving tamper-proof and shared cost data through distributed ledger technology.