Maximizing efficiency in manufacturing is crucial for staying competitive in today’s fast-paced industrial environment. In this article, we dive into the analysis of a production line, focusing on industrial process optimization to boost capacity and minimize costs.
In our case study, a manufacturing company produces components for the automotive industry. These components consist of three parts—A, B, and C—sourced externally at respective costs of $0.40, $0.35, and $0.15 per unit. The goal is to streamline the production process, reduce operational costs, and eliminate the bottleneck in the production bottleneck analysis.
The assembly lines involves three stages in his Process flow:
Initially, the plant operates 8 hours a day, 5 days a week, but increasing demand prompts the possibility of adding a second shift. By calculating the weekly production capacity for each stage, we identified that the first assembly line, with its capacity of 5600 components per week, is the initial bottleneck in the system.
To increase capacity, the company considers two scenarios:
Cost is another critical factor in industrial process optimization. The cost of labor is $0.30 per unit for each assembly line and $0.15 per unit for the drilling process, with electricity costs at $0.01 per unit. Additionally, the company incurs a fixed weekly cost of $1200.
For Scenario A, producing 8000 components per week results in a total weekly cost of $14,480, while Scenario B, with 9600 components, costs $17,136. Analyzing these numbers helps management decide the most efficient and cost-effective strategy for scaling production.
As part of the automation in manufacturing strategy, the company evaluates whether it should continue producing part C or buy it pre-drilled at $3 per unit. With the fixed cost of each drill at $30,000 and considering the company’s use of four drills, the break-even point is calculated at 4460.96 units annually. If the company produces more than 4461 units per year, it is more cost-efficient to produce part C in-house.
The analysis of industrial process optimization in this case study highlights the importance of evaluating both production capacity and cost factors to eliminate bottlenecks. By identifying the bottleneck, management can make informed decisions about capital investments, labor shifts, and automation strategies. Implementing the right solution improves manufacturing efficiency and positions the company for future growth.
For more insights on manufacturing optimization, stay tuned to our blog for the latest strategies in industrial process improvement.