Capacity analysis
Capacity analysis is a method that allows the examination and determination of parameters relating to different types of capacity and capabilities for general transmission and movement in a specific time unit [1]. Capacity analysis is used for the needs:
- transport,
- IT
- management.
Capacity Analysis in Transport
Transport capacity is the maximum transport capacity of a means of transport in a given period of time, in specific conditions defined by current technical and organisational factors. Technical factors determine the payload or load capacity of the means of transport, the speed of the vehicle or the type of vehicle transported [2]. Organisational factors depend on the speed of loading and unloading, the route of the means of transport and the degree of utilization of the payload [3].
Capacity meters
The main measure characterising passenger transport of each type is capacity, defined as the product of the number of passengers (train, bus) and the distance travelled by them. The unit of transport work is the passenger-kilometre [4]. However, the complexity of passenger traffic makes this meter a synthetic one, not reflecting the actual complexity of the movement of vehicles. Therefore, in the case of a number of factors must be taken into account when calculating the transport work for a train as an example, such as [5]:
- the distance travelled,
- wagon class
- type of passenger traffic.
Assumptions for capacity analysis
The concept of capacity in passenger traffic (e.g. rail) can be defined as the number of passengers that is movable in a given period of time, taking into account the convenience of travel [6]. Determination of seating capacity passenger coaches may concern the whole railway network, or only the line or section to be analysed [7].
Calculation of capacity
The following formula may be used to calculate the seating capacity [8]:
whereby:
- Np - number of trains running on a given line,
- nw - number of wagons in one train,
- nm - number of seats in one car,
- Wp - coefficient of utilisation of wagon capacity
- ls - Average distance of a train running on a given line,
- lp - Average travel distance of one passenger.
For example:
- Number of trains running on the line: Np= 36 trains/day
- Average number of wagons of 1st class in one train: nw= 1,19 wagons
- Average number of wagons of 2 classes in one train: nw= 4,64 wagons
- Number of seats in a Class 1 car:
- nm= 9 compartments • 5 seats = 54 seats
- Number of seats in a Class 2 car:
- nm= 10 compartments • 8 seats= 80 seats
- Average train running distance on a given line: ls = 2764/18 = 153,56 km
The wagon capacity utilisation factor is the quotient of the number of passengers in the wagon and the number of seats in the wagon [9]. When determining the maximum capacity of rolling stock, it is assumed that all the seats in the train are occupied, and therefore the coefficient value is Wp=1 However, when determining the level of capacity utilisation of rolling stock, it is necessary to determine the coefficient on the basis of the current train turnout and to calculate its average value [10]. Let the exemplary average distance of one passenger is lp=63 km. On the basis of the above data, the maximum capacity of 1st and 2nd class cars and the total capacity for both classes of cars can be calculated.
- Zol1= 36• 4, 64 • 80 • 1 • 153,56/63 = 32606 passengers 1 class/day.
- Zol2 = 36• 1,19 • 54 • 1•153,56/63 = 5644 passengers 2 class/day.
- Zol = Zol1+ Zol2 =32606 + 5644 = 38250 passengers /day.
Capacity analysis in determining congestion and bandwidth
Capacity analysis is also used to traffic measurements, determine congestion and bandwidth. In a stochastic concept of highway bandwidth analysis, the capacity of an object on a highway is treated as a random variable, not a constant value. In this way, the stochastic approach provides new measures of traffic flow performance based on traffic reliability aspects [11]. A method for estimating bandwidth distribution functions based on empirical data based on statistical methods for the analysis of lifetime data is introduced. This method has been developed for the analysis of motorway throughput. However, it has been shown that the stochastic approach is also applicable to intersections [12].
Capacity Analysis in IT
Each computer is equipped with memory, i.e. electronic systems for storing data and programs. Memory is an ordered (numbered from 0) set of elementary memory cells of a specified length. RAM (Random Access Memory) is a memory with free access (access to any RAM cell is possible at any time). RAM is an internal, operating memory, data can be read and written from it. It contains the data necessary to perform calculations and the results of these calculations. This memory is ephemeral, i.e. when the computer is shut down by any means, the information contained in the RAM is lost [13]. Data from internal memory can be protected against loss by storing them in external memory, e.g. on a hard drive. Particular types of RAM differ from each other[14]:
- capacity, read/write speed, power consumption and voltage needed to power them.
Bandwidth is the ability to transfer data in a time unit. Actual frequency is the actual data rate of the computer. To calculate the bandwidth, you need to know the effective frequency and multiply it by the width of the data bus (or vice versa). Example for DDR-400 memory [15]. Capacity = 400MHz * 64b = 400MHz * 8B = 3 200MHz * B = 3 200MB/s
Capacity Analysis in Management
Capacity in management is understood as efficiency, effectiveness and potential [16]. It is a result of undertaken actions, described by the relation of the achieved effects to the incurred outlays. It means the best effects of production, distribution, sales or promotion, achieved at the lowest costs, such as economy, enterprise, process, finance, management, investment or motivation [17]. Capacity determines the functioning of an organisation and determines its development. It is an important tool for measuring management effectiveness. It covers the phenomena inside and outside the organization. It shows the speed of reaction to challenges that flow from the market, as well as the expectations of its participants. Capacity is also a measure of effectiveness and efficiency, understood as a measure of the extent to which the set goals are achieved [18]. Capacity is measured using partial indicators characterising the effectiveness of particular production factors, e.g. labour productivity or capital productivity, and synthetic indicators of the effectiveness of the entire enterprise, e.g. return on capital, assets, sales. Capacity can be identified ex post and ex ante [19]. When calculating ex ante capacity the expected effects are estimated with the use of specific resources and time, while ex post Capacity is determined by the results of specific actions [20].
Author: Natalia Chowaniak
Examples of Capacity analysis
- Capacity analysis is commonly used in logistics, transportation, and supply chain planning to determine the optimal number of resources needed to move a certain amount of material over a period of time. For example, a company may use capacity analysis to determine how many trucks are needed to move a certain amount of goods from point A to point B within a given time frame.
- Capacity analysis is also used in manufacturing to determine the most efficient way to produce a certain amount of products. For example, a manufacturing company might use capacity analysis to determine the number of machines, workers, and other resources necessary to produce a certain amount of products within a given period of time.
- Capacity analysis can also be used in software development to determine the number and types of resources needed to develop a particular software project within a specific timeline. For example, a software development team might use capacity analysis to determine the number of programmers, designers, and testers necessary to develop a software project within a given timeline.
Advantages of Capacity analysis
Capacity analysis has several advantages.
- It can help identify inefficiencies in the current system, leading to improved operational performance.
- It can provide an understanding of the capacity of a system at any given time, allowing for the development of proactive strategies to mitigate delays or problems.
- It can also help identify the need for additional capacity, such as additional personnel or equipment, allowing for a more efficient system.
- Finally, capacity analysis can be used to assess the impact of changes in external factors, such as weather, on capacity, leading to better decisions and more efficient operations.
Limitations of Capacity analysis
Capacity analysis is a useful tool to determine the capacity and capabilities of transmission and movement, however, there are a few drawbacks to consider. These include:
- Limited visibility: Capacity analysis may not be able to identify the underlying causes of capacity issues or problems, such as bottlenecks or inefficiencies.
- Time-consuming: Capacity analysis is time - consuming and resource-intensive, as it requires significant data collection and analysis.
- Cost: The cost of implementing capacity analysis can be high, as it requires a significant investment in software and hardware.
- Difficulty in assessment: Capacity analysis can be difficult to assess, as it involves analyzing data from multiple sources and understanding the underlying dynamics of the system being studied.
- Subjective nature: Capacity analysis is subjective in nature, as it relies on the analyst’s interpretation and understanding of the data.
Capacity analysis is an important tool for examining and determining the parameters that affect different types of capacity and capabilities for general transmission and movement in a specific time unit. Besides capacity analysis, there are other approaches that can be used to analyze and evaluate the capacity of systems and organizations. These include:
- Capacity Planning: This involves mapping out the resource requirements and capacities needed to ensure successful delivery of products and services.
- Capacity Modeling: This is a process of analyzing the capacity of a system by modeling its components and their interactions.
- Capacity Benchmarking: This involves comparing the performance of the system against industry standards or against other similar systems in order to identify areas of improvement.
- Capacity Optimization: This requires making adjustments to the system in order to increase its efficiency and capacity.
In summary, capacity analysis is an important tool for examining and determining the parameters that affect different types of capacity and capabilities. It is important to consider other approaches such as capacity planning, modeling, benchmarking, and optimization when evaluating the capacity of a system or organization.
Footnotes
- ↑ M. O’Neill, G. Warren, 2016, p.1
- ↑ M. O’Neill, G. Warren, 2016, p.2-4
- ↑ M. O’Neill, G. Warren, 2016, p.2-4
- ↑ R. Chambers 2018, p.13-16
- ↑ R. Chambers 2018, p. 13-16
- ↑ M. O’Neill, C. Schmidt, G. Warren 2016, pp. 18-21
- ↑ M. O’Neill, G. Warren, 2016, p.5-6
- ↑ M. Vangelisti, 2006, pp.44-50
- ↑ KJ. Cremers, Martijn, A. Petajisto, 2009, pp. 3329-3365
- ↑ KJ. Cremers, Martijn, A. Petajisto, 2009, pp. 3329-3365
- ↑ M. Vangelisti, 2006, p. 50
- ↑ M. Vangelisti, 2006, p. 50
- ↑ M. O’Neill, C. Schmidt, G. Warren 2016, pp.18-21
- ↑ M. O’Neill, C. Schmidt, G. Warren 2016, pp.18-21
- ↑ M. O’Neill, C. Schmidt, G. Warren 2016, pp.18-21
- ↑ M. O’Neill, G, Warren, 2016,p.4
- ↑ M. O’Neill, G, Warren, 2016b,p.4
- ↑ M. O’Neill, G, Warren, 2016,p.5
- ↑ KJ M Cremers, A. Petajisto, 2009, p.6
- ↑ KJ M Cremers, A. Petajisto, 2009, p.6
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| Capacity analysis — recommended articles |
| Process performance — Cost model — Structural productivity — Cost avoidance — Productivity report — Quality loss function — Process capability — Organizational techniques — Maintenance strategy |
References
- Chambers R., (2018), Climate Vulnerability and Capacity Analysis Handbook,CARE International p.2, 13-16.
- Cremers, KJ M., Petajisto, A.(2009), How active is your fund manager? A new measure that predicts performance. Review of Financial Studies, 22(9), pp.6,3329-3365.
- O’Neill, M., Warren, G, (2016), Evaluating fund capacity: Issues and Methods.CIFRWorking Paper, No. 124/2016, p.5-6 21-23.
- O’Neill, M., Warren, G,(2016), Capacity Management for Institutional Asset Owners. CIFR Working Paper, No. 125/2016, p.2-4.
- O’Neill M., Schmidt C., Warren G., (2016), Analysis, Research Working Paper No. 129/2016, pp.2-4, 18-21.
- Vangelisti, Marco (2006), The capacity of an equity strategy.The Journal of Portfolio Management, 32(2), pp.44-50.
