Reliability evaluation in the production process of aluminum castings

Boosting Aluminum Casting Reliability: A Data-Driven Look at Productivity and Defects

This technical summary is based on the academic paper "Reliability evaluation in the production process of aluminum castings" by Erika Jankajová and Martin Kotus, published in PRODUCTION ENGINEERING ARCHIVES (2015).

Keywords

• Primary Keyword: Aluminum Casting Reliability
• Secondary Keywords: die casting, production process, productivity evaluation, nonconformities, spoilage rate

Executive Summary

• The Challenge: Maximizing economic efficiency in die casting is hampered by inconsistent productivity and spoilage rates across different work shifts.
• The Method: The study analyzed the number of parts, productivity rates, and nonconformities for a specific aluminum cast part over a full workweek, encompassing 15 distinct shifts.
• The Key Breakthrough: The night shift consistently produced the fewest parts and had the highest nonconformity rate (5.42%), while Tuesday shifts achieved the highest productivity (97.05%) with the lowest nonconformity rate (2.95%).
• The Bottom Line: Optimizing aluminum casting reliability requires a targeted approach to managing shift-specific and day-specific factors that directly influence both production output and quality.

The Challenge: Why This Research Matters for HPDC Professionals

In today's competitive manufacturing landscape, economic efficiency is paramount. For high-pressure die casting operations, this efficiency is directly tied to two key metrics: the number of quality parts produced per shift and the rate of internal spoilage. Manufacturing batches that fail to meet quality requirements are useless, representing a significant loss of time, material, and resources.

While factors like mould design and temperature control are known to be critical for quality, this study addresses a more granular operational challenge: understanding how production reliability fluctuates under real-world conditions. The research aims to provide a reliable evaluation of a manufacturing process by monitoring and analyzing productivity and spoilage, offering a clear window into the variables that impact the bottom line.

The Approach: Unpacking the Methodology

The evaluation was conducted at MOPS PRESS, Ltd. in Snina, an organization specializing in die-cast aluminum alloy parts.

• The Component: The study focused on a specific part identified as "Lagerschild AS," an electrometer panel manufactured for BOSCH & SIEMENS washing machines.
• The Equipment: A fully automated workstation (L20-630.05) was used, featuring a CLH 630.05 die casting machine, a batching furnace, and a robot for part removal, cooling, and transport to the shearing operation. The process cycle—from mould closing to shearing—is automated with minimal operator interference.
• Data Collection: The research team monitored production over a full five-day workweek, covering morning, afternoon, and night shifts for a total of 15 observation periods. Data on the number of cast parts produced, productivity (percentage of good parts), and nonconformities (percentage of spoiled parts) were collected and averaged for each shift.

The Breakthrough: Key Findings & Data

The study revealed clear patterns in production output and quality that varied significantly depending on the time of day and the day of the week.

Finding 1: The "Night Shift Effect" on Production Volume and Defects

The data clearly shows that the night shift is the least efficient period of production. As detailed in Table 1, the night shift produced the fewest parts on average (1,632 pieces) compared to the morning (1,900 pieces) and afternoon shifts (1,989 pieces). Critically, this lower output was accompanied by the highest rate of nonconformities, averaging 5.42%. In contrast, the morning shift achieved the lowest nonconformity rate at 3.46%. This indicates a systemic issue impacting both quantity and quality during late-night operations.

Finding 2: A Surprising Link Between Productivity and Day of the Week

Analysis of the full workweek revealed a non-linear relationship between output, defects, and overall productivity. According to Table 1, Tuesday was the most efficient day. While total parts produced were the lowest for the week (4,780 pieces), the nonconformity rate was also at its lowest (2.95%), resulting in the week's highest overall productivity of 97.05%. Conversely, Friday saw the highest number of parts produced (5,980 pieces) but also suffered the highest nonconformity rate (5.75%) and the lowest overall productivity (94.25%). This suggests that pushing for maximum output toward the end of the week may come at the cost of quality.

Practical Implications for R&D and Operations

• For Process Engineers: This study suggests that shift changes, particularly the transition to and during the night shift, are critical control points. The data justifies a deeper investigation into variables that may differ at night, such as ambient temperature fluctuations, machine parameter drift, or operator fatigue.
• For Quality Control Teams: The data in Table 1 and Figure 4 illustrates a clear pattern of defect rates varying by shift and day. This could inform a more dynamic quality inspection strategy, with increased monitoring frequency and scrutiny applied to parts produced during the night shift and later in the workweek.
• For Design Engineers: The paper's introduction highlights that an "optimum temperature of each surface part of the mould cavity" is an important prerequisite for quality. The process variability observed across different shifts underscores the need for robust mould designs with excellent thermal management to minimize the impact of external variables and maintain process stability.

Paper Details

Reliability evaluation in the production process of aluminum castings

1. Overview:

• Title: Reliability evaluation in the production process of aluminum castings
• Author: Erika Jankajová, Martin Kotus
• Year of publication: 2015
• Journal/academic society of publication: ARCHIWUM INŻYNIERII PRODUKCJI / PRODUCTION ENGINEERING ARCHIVES
• Keywords: production process, die casting, aluminium castings

2. Abstract:

This article deals with reliability evaluation of the production process for die casting. Reliability of the production process was assessed on the basis of productivity and deformity. With suitably chosen production technology the increasing of labour productivity can be achieved alongside the required quality of aluminum castings.

3. Introduction:

Currently, each manufacturing organization resists constraints and threats within its competitors. The key factor for cheaper, superior, and more productive manufacturing is knowledge transfer from the field of science and technical progress. Numbers of cast parts within a work shift as well as number of cast parts which meet quality requirements represent the decisive influence on economic efficiency of die casting. Therefore, internal spoilages are also evaluated by number of parts from manufacturing batches that do not comply with quality requirements so, they are useless. The quality of casts is affected not only by the design solution but also the reliability of permanent moulds. The lifetime of mould depends on the influence of temperature factors for die casting. An important prerequisite for quality cast production is keeping an optimum temperature of each surface part of the mould cavity. The study aims at a reliable evaluation of the manufacturing process on the basis of assessment of aluminium cast parts manufactured by die casting. Manufacturing process quality is evaluated through monitoring and analysing productivity and spoilages of particular cast parts.

4. Summary of the study:

Background of the research topic:

The research is set against the backdrop of competitive manufacturing, where economic efficiency in die casting is determined by the output of quality parts and the minimization of spoilage.

Status of previous research:

The introduction cites previous work highlighting the importance of knowledge transfer for productivity (TOLNAI R. 2002), the evaluation of internal spoilages (PETRÍK M., KOTUS M. 2009), and the critical role of mould temperature in producing quality casts (MATISKOVÁ D. 2012; MATISKOVÁ D., GAŠPAR Š., MURA L. 2013).

Purpose of the study:

The study aims to conduct a reliable evaluation of a die casting manufacturing process by assessing the productivity and spoilage of aluminum cast parts.

Core study:

The core of the study involved monitoring an automated die casting workstation over a full workweek (15 shifts) to collect data on the number of parts produced, productivity rates, and nonconformity rates for the "Lagerschild AS" aluminum part.

5. Research Methodology

Research Design:

The study used an observational research design within an active industrial manufacturing environment. Data was collected over a defined period (one workweek, three shifts per day) to capture operational variability.

Data Collection and Analysis Methods:

The number of cast parts was determined from the dispatch note card for each manufacturing batch. Time was observed for 10 cycles during each of the 15 shifts. The collected values for cast parts, productivity (%), and nonconformities (%) represent the averages for the period under consideration.

Research Topics and Scope:

The research was conducted at the organization MOPS PRESS, Ltd. in Snina, focusing on the production of a single component, "Lagerschild AS," on workstation L20-630.05. The scope was limited to a one-week observation period.

6. Key Results:

Key Results:

• Over the week, 27,604 pieces were produced with an average productivity of 95.58% and an average nonconformity rate of 4.42%.
• The afternoon shift was the most productive in terms of volume (average 1,989 pieces), while the night shift produced the least (average 1,632 pieces).
• The night shift had the highest rate of nonconformities (5.42%), while the morning shift had the lowest (3.46%).
• Tuesday had the lowest nonconformity rate (2.95%) and highest productivity (97.05%).
• Friday had the highest nonconformity rate (5.75%) and lowest productivity (94.25%).

Figure Name List:

• Fig. 1 Cast Lagerschild AS
• Fig. 2 Production machine for Workstation L20-630.05
• Fig. 3 Productivity of the cast parts manufacturing process on the workstation
• Fig. 4 Nonconformities of the cast parts manufactured on the workstation

7. Conclusion:

The automated manufacturing process is classified as suitable and effective, achieving an overall productivity of 95.58%. However, the data reveals significant performance differences between shifts, with the night shift being the least reliable in terms of both output and quality. The lowest nonconformities are achieved in the morning shift, influenced by both objective and subjective causes. The study concludes that productivity can be improved by maintaining consistent manufacturing methods and implementing measures to decrease nonconformities, especially during identified periods of low performance.

8. References:

1. KOTUS M., KOVÁČ I., PETRÍK M., KOVÁČ J. Production of aluminium casts through casting under pressure. (Výroba hliníkových odliatkov pomocou tlakového liatia). In Quality and Reliability of Technical Systems. Nitra : SUA, 2009. p.176-180. ISBN 978-80-552-0222-8.
2. MATISKOVÁ D., GAŠPAR Š., MURA L. Thermal Factors of Die Casting and Their Impact on the Service Life of Moulds and the Quality of Castings. In Acta Polytechnica Hungarica, Vol.10, No.3, 2013. p.65-78. ISSN 1785-8860.
3. MATISKOVÁ D. The Methodology of Economics Costs Influential on Automation of Component Production. In American Journal of Economics. No. 7, 2012. p.164-170. ISSN 2166-496X.
4. PETRÍK M., KOTUS M. Automation of casting under pressure in the production process. (Automatizácia tlakového liatia vo výrobnom procese). In Safety – Quality – Reliability. Košice : TU, 2009. p.173-177. ISBN 978-80-553-0137-2.
5. TOLNAI R. Engineering Technology. (Strojárska technológia). Nitra : SUA, 2007. p.319. ISBN 978-80-8069-842-3.

Expert Q&A: Your Top Questions Answered

Q1: Why was the "Lagerschild AS" part chosen for this study?

A1: The paper identifies this part as a component for an electrometer panel used in automatic washing machines for BOSCH & SIEMENS. Choosing a real, high-volume industrial part ensures that the findings on productivity and nonconformities are directly relevant to real-world manufacturing challenges, not just theoretical or laboratory conditions.

Q2: The paper mentions "subjective causes" affecting nonconformities in the morning shift. What might these be?

A2: The paper states the least nonconformities are noted in the morning shift, which is "affected not only by objective causes, but also by subjective causes of employees, quality manager or employer." While it doesn't specify what these are, this suggests that human factors such as operator alertness, higher levels of supervision, or management presence at the start of the workday may contribute positively to quality outcomes.

Q3: Table 1 shows Tuesday had the lowest total output of the week (4,780 parts) but the highest productivity (97.05%). How is this possible?

A3: Productivity in this study is defined as the percentage of cast parts that meet quality requirements, not just the raw number of parts produced. Therefore, while the total output on Tuesday was lower, a significantly higher percentage of those parts were free of defects (only 2.95% nonconformities). This resulted in less waste and higher overall process efficiency for that day.

Q4: What specific types of "nonconformities" were being measured?

A4: The paper assesses reliability on the basis of "productivity and deformity" and evaluates "internal spoilages," but it does not provide a breakdown of the specific defect types (e.g., porosity, cold shuts, cracks). The analysis focuses on the overall rate of parts that "do not comply with quality requirements," treating nonconformity as a single, aggregate metric.

Q5: The study concludes the automated process is "suitable and effective," yet nonconformity rates reached 5.75% on Friday. How is this reconciled?

A5: The conclusion likely classifies the process as "suitable and effective" because the overall weekly productivity is high (95.58%) and the system is automated with minimal operator intervention. The value of the study is not to condemn the process, but to identify specific periods of weakness (like the night shift and end-of-week production). This allows for targeted improvements to raise the reliability of an already effective system.

Conclusion: Paving the Way for Higher Quality and Productivity

This study provides a crucial reminder that even in highly automated environments, operational variables can have a profound impact on Aluminum Casting Reliability. The clear correlation between work shifts, day of the week, and defect rates demonstrates that achieving peak efficiency requires more than just a well-designed machine and mould. It demands a holistic understanding of the entire production ecosystem.

The findings—particularly the challenges of the night shift and the quality trade-offs at the end of the week—offer a data-backed roadmap for process improvement. By focusing on these specific periods, manufacturers can implement targeted strategies to stabilize their process, reduce waste, and enhance overall productivity.

"At CASTMAN, we are committed to applying the latest industry research to help our customers achieve higher productivity and quality. If the challenges discussed in this paper align with your operational goals, contact our engineering team to explore how these principles can be implemented in your components."

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• This content is a summary and analysis based on the paper "Reliability evaluation in the production process of aluminum castings" by "Erika Jankajová, Martin Kotus".
• Source: http://www.qpij.pl

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