Strategic Facility Location and Capacity Planning

Posted on Jan 3, 2025 in Economy

Introduction

Enterprises operate in various facilities, including processing plants, assembly lines, warehouses, stores, after-sales support centers, and offices. These facilities result from interconnected decisions. The type of facility depends on the product or service offered and the production process or technology used. The size depends on the required capacity. Other key decisions include the location and layout. This document discusses the main issues affecting facilities:

• What kind of facilities are required?
• What size should they be?
• Where should they be located?
• What should be the internal distribution of elements?

Location Decisions

Location decisions are strategic for a company. A good location can help achieve business goals, while a poor one can hinder operations. This section examines the role of location in operational subsystem design, the decision-making process, and key influencing factors. We will also explore mathematical tools for selecting the most suitable location.

Causes, Importance, and General Procedure for Making Decisions

Location decisions are generally infrequent, especially for small, local businesses. However, for others like banks, chain stores, and hotels, they are more common. Several factors can trigger location reviews, such as market expansion, new product launches, demand shifts, obsolescence, competition, and mergers. Regardless of the cause, location alternatives fall into three categories:

• Expanding an existing facility: This is viable if there is enough space and the current location is suitable. It is often cheaper, especially if expansion was planned.
• Adding new facilities in new locations: This may be more advantageous if expansion causes problems or distracts from operational goals. It is sometimes the only option. The impact on the entire company system must be considered.
• Closing facilities and opening elsewhere: This can be costly, so the benefits of relocation must be weighed against remaining at the current site.

The Importance of Location Decisions

Selecting a site for operations is a critical decision. Although rare, its impact warrants careful consideration by the board. The unusual nature of these decisions means many managers lack experience with them. This importance is justified for two main reasons. First, location decisions involve a significant long-term financial commitment. Facilities are generally expensive, especially sophisticated manufacturing plants. Once built, the investment is difficult to recover without severe economic damage. Therefore, it is a long-term commitment. Second, these decisions affect the company’s competitiveness. A good choice will foster efficient and competitive operations, while a poor one will impose limitations. All areas of the company, not just operations, can be affected. The negative consequences of a bad location are not always obvious, often appearing as opportunity costs. Location influences competitiveness through both costs and income. Proximity to markets is critical for utilities, while for manufacturing firms, it affects delivery times and service levels. Location can also influence costs related to land, labor, raw materials, and distribution.

These considerations show that location selection requires proper attention from the board and all involved business areas.

The Location of Facilities and Operations Objectives

The overall goal of localization is to choose a location that promotes the development of operations. This goal translates into localization strategies that vary greatly between companies, even within the same sector, due to different competitive priorities and operations strategies. A public or non-profit enterprise may prioritize customer service over cost containment, leading to different location strategies than a for-profit enterprise. A firm seeking cost leadership will settle where costs are lower. However, if other strategic priorities exist, decisions may differ, favoring better service levels, reduced delivery times, skilled labor, or higher quality materials. Location decisions are part of the design decisions and are conditioned by all the strategies in this field. An industrial company might choose between maintaining few large plants or many smaller ones. This choice involves a trade-off between transportation costs and facility costs. The ideal point is where total costs are minimized. However, cost is not the only variable. A greater number of facilities closer to the customer leads to shorter delivery times and better service. The theoretical optimum number of installations from a cost perspective may not align with other goals. The choice should consider both the achievement of objectives and their priorities.

N º FACILITIES

N º FACILITIES

COST installation. ” Installation Do IINSTALACION

FACILITIES

TRANSPORT COSTS. TRTRTRANSPORTE TRATRANSPORTE

TRANSPORT

COST

TOTAL

LEVEL OF SERVICE

General Procedure for Making Location Decisions

1) Preliminary Analysis: Study business strategies and policies to translate them into location requirements. Determine the important criteria for evaluating alternatives: transportation, land, supplies, personnel, infrastructure, environmental conditions, etc. Assess the importance of each factor, distinguishing between dominant, key, and secondary factors. Dominant factors derive from strategic objectives and have a great impact on income, costs, or competitive position. Secondary factors are desirable but not essential.

2) Finding alternative locations: Identify candidate locations, rejecting those that do not meet the company’s dominant factors (e.g., resource availability, skilled labor, market potential, stable political climate).

3) Evaluation of alternatives (detailed analysis): Collect information about each location to measure it against each factor. This assessment may be quantitative (e.g., transport costs) or qualitative (e.g., political climate).

4) Selection of location: Compare alternatives using quantitative and qualitative analysis to determine valid locations. The objective is to find acceptable locations, not necessarily the optimal one. Subjective factors, such as the board’s preferences, may determine the final location.

Trends and Future Strategies in Location

Most location factors change over time. The rapid pace of environmental changes makes location decisions more common. Key changes include:

The growing internationalization of the economy. Companies compete globally, and locations outside their home countries are common. New markets emerge, and others unify. This intensifies competition, making logistical factors more complex and forcing companies to reconsider facility locations.

Automation of processes in some industries reduces the importance of labor costs, making low-wage countries less attractive. The qualification, flexibility, and mobility of labor are becoming more significant. However, labor costs remain fundamental in some industries, leading to moves to countries with lower wages. For example, Mexico has seen an influx of Japanese, European, and American companies due to low wages and its inclusion in NAFTA.

Improved transportation and the development of information technologies and telecommunications are aiding the internationalization of operations and enabling greater geographical diversity in location decisions. This, coupled with greater emphasis on customer service, is leading to a tendency to locate closer to markets. Flexible technologies allow companies to install numerous small plants.

Improved telecommunications allow the centralization and enlargement of certain operations. Many service companies can reach customers over long distances. Manufacturing companies may outsource production, not needing to own facilities. This practice is called a dematerialized firm or network enterprise.

Adoption of JIT systems in some industries is forcing suppliers and customers to locate nearby to reduce transport times and make frequent deliveries.

Some Quantitative Methods for Localization

This section focuses on mathematical techniques for comparing alternatives and selecting a location. These methods are simple and general, making them suitable for various situations. They are useful for initial assessments or to limit the search for solutions. They tend to focus on partial aspects of the decision problem. Techniques that incorporate subjective judgments and combine them with quantitative factors are also important.

Graphs of Volumes, Revenues, and Costs: Analysis of the Impasse

Location can affect both costs and revenue. Graphic analysis can help compare alternatives, considering both factors for different production and sales volumes.

Income may be affected by location when the ability to attract customers depends on proximity, as is often the case with utilities. For industrial firms, this is less frequent.

In terms of cost, the analysis distinguishes between fixed and variable costs, which can vary by location. Fixed costs include the acquisition cost of installation, land, construction, or rental. Variable costs include labor, raw materials, and transport costs. Rarely is one alternative better than others in terms of both revenues and costs. Graphs can help compare location alternatives, but their limitations must be considered.

SAMPLE

A service company is analyzing two locations, A and B. Location A offers lower fixed costs but higher unit variable costs. Income is the same for both options, but sales volume will vary with location. In this case, the difference in income exceeds the difference in total costs, making alternative A preferable.

EXAMPLE:

A company intends to choose a location for a manufacturing plant based on costs, as sales revenue will not be affected. The company is studying four alternatives with the following fixed and variable costs:

Option A has lower fixed costs, but higher variable costs. Location B has cheaper labor and supplies. Location C has higher fixed costs but the lowest variable costs. Location D is intermediate in both fixed and variable costs.

The representation of the cost functions shows the most convenient alternative for each level of demand. Alternative A is best for volumes up to 100, B for values between 100 and 150, and C for figures above 150. Alternative D is always overtaken by the others.

Method of Center of Gravity

This simple method is limited to a single location factor: the cost of transport. It is used for locating manufacturing plants or distribution warehouses based on points of origin and destination. The problem is to find a central location that minimizes total transport cost (CTT). CTT is proportional to the distance traveled and the size or weight of materials transported. CTT = å c _i v _i d _i, where c _i is the unit transportation cost, v _i is the volume or weight of materials, and d _i is the distance. The product c _i v _i is the weight, w _i, or importance of each item.

Distances can be measured on a map using a coordinate axis system. The two most used measures are:

• The rectangular distance: when journeys are made through 90° turns. This measure could be used for a location within a city. d _i = K (ex-x _i e + e – and _i ê) [1]
• Euclidean distance: the straight line connecting point i to the place occupied by the installation. d _i = K [(x-x _i)² + (y – y _i)^{2] 1 / 2} [2]

Both are approximations, but the errors are similar for all locations. To reach the optimal location, start with a good initial solution by calculating the center of gravity. The coordinates are given by:

[3]

This section does not necessarily correspond to the optimum for any of the previous distance measurements, but it is a fairly good, which could be accepted as a solution to the problem. If want more precision, incremental calculations could be made as follows: the solution moves a little distance in all directions (north, south, east and west) and check if the cost decreases in any of them, if this does not happen, it would be optimal, but otherwise would keep moving in that direction that reduces the cost, the process is repeated as many times as necessary.

In the case of using rectangular distances, the optimal solution can be found through a simple median model:

1. Identify the average value of displaced quantities weighted by their costs, c _i v _i / 2.
2. Rank points according to their abscissa, accumulating weighted charges.
3. The ordinate and abscissa where the average value is included will determine the optimum point.

EXAMPLE:

A new plant location is sought to minimize transportation costs. The sources of supply, F _i, and the destinations, M _j, are shown in the chart. The table shows the average quantities transported per month, v _i, the unit costs, c _i, and the product of both. Assuming rectangular distances, the optimum location is determined.

From the sum of the products, c _i v _i, calculate the average weight:

c _i v _i / 2 = 82,000 / 2 = 41,000

Points are arranged in increasing order of their abscissae and ordinates. The point where the aggregate amount first exceeds the average value is the optimum point (15, 30).

If Euclidean distances are used, the optimum would be in the coordinates:

[4]

However, such expressions can not directly supply the solution, which must be obtained by successive approximations (see Example continuacióndel above). To begin, we calculated the center of gravity as defined in [March], the solution was taken for calculating the distances d _i through the expression [2], then substituting in [4] to obtain new values of x y. The process will continue in an iterative fashion until the coordinates do not change from one iteration to another or until the change seems insignificant enough to not more similar interests.

SAMPLE

Following the example above, the center of gravity resulting from applying the expressions [3] would be:

x * = 2.792.500/82.000 = 34.054

y * = 3.607.500/82.000 = 43.993

Thus, if the facility is located at that point (34, 44), it will be possible to calculate the Euclidean distances to each point through the expression [2] thus yields the following table, which has been also calculated the total cost of transportation, CTT, which would result from that location:

With the distances calculated, di, would proceed to determine the new center of gravity by the expression [4], which begins an iterative process, through which again would be calculated distances and with them a new center of gravity, …

The solution to the example gives us the optimum point (40.30), just where is the supply center F1. This has occurred at iteration 54 where the total cost is stabilized at 3,264,133 um

As we have seen the method described is quite simple since it requires data or difficult to obtain or complex calculations. This makes it very easy to use and appropriate, therefore, to obtain, quickly and economically, an initial approach to the choice of location. It can be used to define the area in which, subsequently, from other criteria, will seek alternative sites considered as only one of many factors to analyze.

2.2.3.3 .- Method of transport.

This technique is an application of linear programming problems of a type with particular characteristics. It is considered that there Unare of factories, warehouses or any other type of points, origins and destinations of flows of goods. The location of new points in the network affects all of it, causing reallocations and adjustments within the system. The method of transport allows you to find the best distribution of flows above basis, usually in the optimization of transportation costs (or, alternatively, of time, distance, profit, etc.).. In location problems, this method can be used to analyze the best location for a new center, several at a time and, in general, for any network reconfiguration. In any event, should be applied to each of the alternatives to considerarpara determine the optimal flow allocation.

2.2.3.4 .- Method of weighted factors.

It is the general method discussed here because it allows the analysis to incorporate all sorts of considerations, be they quantitative or qualitative. Would be briefly described as follows (see example):

It identifies the most important factors to consider in the decision.

Establishing a balance among them according to their relative importance.

Each alternative is scored for each of these criteria from a predetermined level.

Finally, overall rating is obtained, P _i of each alternative, given the same score on each factor, P _ij and the relative weight of the same, W _j. Accordingly, P w _i = å _j P _ij.

SAMPLE

The study team created for the location of new manufacturing facility has identified a set of important criteria for success of the decision, at the same time, it has awarded the degree of importance of each in terms of percentage. With these criteria were assessed each of the alternatives at a scale of 0-10. All this is reflected in the following table:

The total score for each alternative is calculated as the sum of the scores for each factor weighted according to their relative importance. For example, total score received by the alternative A would be obtained as:

P _A = 7 x 5 x 0.30 + 0.30 + 0.20 + 9 x 6 x 7 x 0.15 + 0.05 = 6.65

Alternatives B, and C appear to be better than A, so it could reject the latter. Among the remaining two, there is a small diferenciaafavor of C, though perhaps not final. We see that C has the major advantage of being very close to the source of supply of raw material, which is an important factor, while its weakness is the cost of installation, which is quite high. For its part, the advantages of B lie in labor costs and installation costs, which are better than those of C. In the other criteria, transport and taxes, both are well matched. In view of this could be offered to address the alternatives B and C as feasible to make this decision based on other elements. However, it should be noted that the alternative B shows no weakness as marked as C, which could swing the solution to your favor.

The example can be seen clearly that the technique is merely exposed formalization of intuitive reasoning process decider. Their main advantage lies in specifying the process for it to be known by all, encouraging debate and consistency in the trial.

2.3 .- The decisions of long-term capacity

Although there are different nuances when speaking of the building, there is a common denominator when defining it. This leads to consider the quantity of product or service that can be obtained in a given production unit during a certain period of time.

In the context of this chapter, set in the design of the production subsystem, we will consider only the long-term capacity (with a time horizon of at least two years), which is mainly marked by the fixed structure of the company. That is why the decisions on changes to long-term capacity of a structural nature are usually involve substantial investment and should be taken at the highest level of Corporate Governance. The importance of this decision is enormous, more so when, once executed, it is difficult to alter without incurring high costs.

We must bear in mind that although a certain amount of fixed structure implies a certain capacity in the long run, it can happen that a company maintain a strategy of outsourcing some of the activities necessary to achieve the final products.

For many companies it is easier to use a measure of aggregate capacity especially clearly repetitive processes, for example, cars / year, barrels of beer, tons of cement per month, miles / year. However, in other circumstances it is difficult to find a common measure clearly representative, for a given capacity can lead to infinite possible combinations in terms of quantity of products or services mentioned. We know that for a given production system, the amount of products or services obtained over a period of time depends on the resources available for their production, therefore we can measure the capacity as the amount of resources available in a certain period of time ( horas-máquina/mes example, man-hours per month, etc.)..

The basic question to solve in making the decision on how and when capacity is needed. It is called Capacity Planning and Control, the continuous adaptation between the available capacity and the necessary, that consists in making the conversion of the plans and programs of production capacity needs to estimate the available capacity and develop relevant measures for compliance of both.

Within the long term, which is the interest in this chapter, the difficulty in the forecast tends to be large (think of the possible evolution of demand for products and services, technology, etc.), What This complicates decisions about capacity. they are usually marked by two possibilities: the expansion or contraction. The contraction, which generally entails closing plants and firing of staff, often used as a last resort. Do not forget that this means sacrificing effort, facilities, human capital and knowledge, etc. As regards the expansion strategy, it should highlight what the first thing to do is to ensure that existing capacity is being used in the best way possible. Consideration should, therefore, if we have a lack of capacity or with a defective use of the same, in which case should proceed first to correct the factors that influence the use of more or less the same.

2.3.1 .- Planning and control of long-term capacity. Aspects of interest.

Recall that the purpose of planning and capacity control is none other than the existing capacity to adapt to the needs arising from the demand to satisfy, and this in the most efficient and economical manner.

The steps to follow in the planning and control process are:

Conduct an assessment of existing capacity and into the future, thus obtaining the availability of it.

To estimate capacity needs in the time horizon chosen, based on forecasts of demand or production schedules to meet for that.

Observe the differences between needs and availability and to identify possible alternatives that would allow removal.

Evaluate the alternatives taking into account the quantitative and qualitative implications of each.

Select an alternative.

Implement and monitor results.

2.3.1.1 .- Calculation of available capacity in the long term.

Once in possession of a correct measure current availability, we make a projection of it into the future according to the time horizon chosen. When it has to be noted that the capacity does not remain constant over time. As regards the long term, two important factors of change are the reduction caused by aging facilities and increase the effect produced by training.

As time passes, increasing the damage to the equipment, these give rise to more defects, they are slower and are wearing out, causing all of this a gradual decrease in capacity. This can be slowed with proper preventive maintenance policy and replacement, based mainly on checking the equipment and replace the vulnerable parts of the same before it crashes, or whenever a certain period elapses, or after a certain time of use.

With respect to learning effect, this implies an improvement in processing time, which occurs as a result of experience in performing tasks (every time i doubling of cumulative production is achieved by a given percentage reduction process time). This effect is usually collected in the so-called learning curves.

2.3.1.2 .- The determination of the capacity needs

Clearly, whether manufacturing companies or services, the basis of sound long-term planning is to have good demand forecasting; this is not easy, especially for that timeframe. We must consider that the time to build but the minimum time that it should “remain economically productive for many years. But who can say that after so long, we will develop exactly the same products or services? Do you keep the tastes of consumers? To answer these questions must be close collaboration with the Commercial Department, which best knows the life cycles of products that fall and Marketing Plans, market research and developing new products together with the Department Research and Development. Furthermore, how can be sure that will be future technologies? Can we ensure that production processes will remain the same? These issues affect how to obtain products and services and thus, the type and amount of capacity required, this shows the importance of anticipating potential introduciruna technological developments in the planning of facilities.

For the calculation of the required capacity can be used numerous techniques that fall outside the margins of the subject, in any case, the calculation of available capacity, should take into account the factors of efficiency and utilization, as well as defective products that prove possible level of quality that characterize the company. In general, if measured in units of resources, the capacity would be obtained as:

The sum of the products of annual demand (in units of products) by the necessary resources for each unit.

But the cushion of capacity.

Divided by the product of the above factors (use and efficiency).

The determination of the needs of long-term capacity, which do not have to be the exact translation of the estimated demand. Sometimes it may happen that there are insufficient resources to meet the latter, in which case it may waive part of it, thereby affecting the capacity. In other cases, however, the company may decide (assuming sufficient resources) to maintain a capacity cushion above the estimate in order to allow, among others, some (s) of the following objectives:

• Having extra capacity for times when demand exceeds expected, which is possible given the randomness of it.
• Ability to meet demand in peak periods.
• Greater flexibility in allowing changes in product requirements or on demand from customers.

Ensure quality levels of products or services, which sometimes deteriorates when working at the limit of capacity.

2.3.1.3 .- Alternatives to bring long-term capacity available to the needed.

For each alternative response is linked to several interrelated questions: how much capacity? What kind? At what point? Where?. The long-term nature of this decision pushes the alternative of flexible facilities that adapt to possible future changes.

In the case of expansion, not mutually exclusive alternatives to adapt to changes in long-term capacity can be:

Build or acquire new facilities, having studied the type, number and size of them and the time of implantation.

Expand, modify and update existing facilities and / or use form, so as to provide greater capacity.

Establish networks of subcontracting for the provision of components or finished products, allowing work with less capacity in the company.

Reopen facilities that are inactive.

In the case of contraction of capacity, possible courses of action include:

• Alternative use part of the premises or place them in reserve so that they remain inactive pending possible later use.
• Sell facilities and inventories and dismiss or transfer labor.

• Develop new products to replace those with declining demand.

2.3.1.4 .- Evaluation of alternatives.

Before assessing the various alternatives must be clear about the different criteria applied. Among them, are particularly important economic and financial, which reflect the desirability of capacity investment decision on that point of view. Graphic techniques such as neutral, the capital value or internal rate of return can be useful for this purpose. Critical factors to consider, according to the method used, would the various cost, revenue and payments, capital value of the option in question, etc..Since such data can hardly be known with certainty, we introduce randomness in the evaluation for this, methods such as decision trees could be useful. The choice of either technique will depend, in any event, the type of problem to solve capacity and the characteristics that define both the company and the environment in which it operates.

However, when assessing the various alternatives should be considered only quantitative criteria and measurable in monetary units. There will always be very important qualitative factors that must be present in making final decisions. Take, for example:

Degree of compatibility with existing staff.

Possible reactions by the public (for example, not be the same to build a hydro plant than a nuclear).

• Responsiveness of the competition.

Risk of technology obsolescence, etc.

2.3.2 .- Some techniques for evaluating alternatives.

2.3.2.1 .- The capital value basis, VC (VAN)

Its application allows to know the total net profit in the investment horizon. It is not our purpose to dwell in the exhibition of this or other investment evaluation criteria (both internal return (IRR), payback period (PR), etc.). We will just briefly formulate and define the explanatory variables:

where:

A: Capital invested (assuming that everything is paid at time zero).

Q _i: net cash flow in year i, equal to the difference between cash receipts from sales and payments under operating expenses in the year.

RV: Residual value of investment in year n.

No: Number of years time horizon.

k: Cost of capital (assumed constant over time.) It serves to update the value of money and be able to refer all quantities to the initial instant.

2.3.2.2 .- Graphs neutral or equilibrium.

The use of this technique for making long-term decisions can be risky. If the problem under study characteristics would suggest that implicit assumptions are true enough in itself, may be used.

2.4 .- Distribution on the ground.

So far, following the design process of the production subsystem, we adopted several decisions on what, how, what and where to produce, and on the capacity of facilities, defining a number of interrelated factors. Now, in addressing the plant layout, when you search their physical implementation, so as to achieve the best performance of the facilities. This applies to all cases where they are needed the provision of physical means in a given area, and this fixed or not, extending its usefulness both industrial and service processes (eg factories, shops, department stores, hospitals, restaurants, offices, etc.). With this in mind, we can define the distribution plant (DP) as the process of determining the best management of available factors, so as to constitute a production system capable of meeting the objectives set in the most appropriate and efficient manner.

2.4.1 .- Objectives of the layout.

The basic objective is to get a good plant layout are:

Unity: We must achieve the integration of all elements or actors involved in the production unit, to be run as a community of purpose. Therefore, all departments must be considered and consulted to undertake the overall phase of distribution, this would facilitate the achievement of a final solution that combines maximum benefits and minimal inconvenience to them.

Minimum movement: we must ensure that the journeys made by men and materials, operation to operation and between departments, are optimal, which requires motion economy, equipment, space, etc..

Safety: This is to ensure safety, staff satisfaction and comfort, thereby achieving a reduction in accident rates and improved working environment. It may seem a cliché but the key to many dealers there lies: “Let the work is done automatically welcome and get many other benefits.”

Flexibility: As we mentioned in the preceding paragraph, the plant layout need more or less frequently, to adapt to changing circumstances under which operations are carried out, which makes it advisable to adopt flexible distributions. These should remain adequate even after significant changes in customer mix, the mix of products / services, space needs in a warehouse or in the organizational structure in an office. In this sense, the flexibility of a DP depends largely on the ability to predict changes. If this is not possible, a flexible should at least allow the changes required by the new conditions can be made at minimal cost.

2.4.2.-Types of plant distribution

Organizational form of the production process, ie, the selected configuration, decisive for the choice of layout. According to the settings we studied in the previous topic, we can distinguish three basic forms of plant distribution:

Product oriented (associated to continuous or repetitive settings): the management of jobs is determined by series of operations to be performed, moving the product from one point to another.

Process-oriented (associated with batch settings) and related equipment operations with a specific type of activity are clustered in certain areas, they pass through various processed products as required or not every activity in question.

For fixed position (associated with Projects configurations).

2.4.3 .-. Analysis of plant distribution by product. The balance of strings.

The crux of the matter lies in the possibility of subdividing the workflow enough for staff and equipment are employed as closely as possible throughout the process. In the frequent case that one of the operations of the process requires more time to be executed than any other, will become what is known as a bottleneck, whose capacity, the lowest of all workplaces, restricts the entire process. This problem is solved by balancing the chain, which is to be divided into work stations whose load is properly adjusted or balanced. The allocation of work to the various stations is performed so as to achieve the desired output with the least number of stations. The concept of equilibrium could be defined later, depending on the time of execution of the tasks. The steps outlined below:

2.4.3.1 .-. Definition of tasks and identification of precedence.

It begins by breaking down work tasks, or the smallest unit that can be done independently. Thereafter, for each, identify the activities above, ie those which are to be made for the task at hand can begin. Although most airlines have to meet certain technical requirements regarding the order of the various activities, there are also cases where there is some freedom to establish more of a sequence of operations. This arrangement is contained in the so-called precedence diagram.

.-. 2.4.3.2 Calculation of minimum number of workstations.

Defined tasks and precedence, the third step is to calculate the minimum number of stations required to produce the product. This begins by calculating the cycle time line, which represents the maximum time allowed to each station to process one unit of product. The expression of cycle time, c, in seconds / unit is: c (sec / one.) = [(1 / r) (h / a.)] X 3600 (sec / h), where r is the production desired expressed in units / hour. To achieve the latter, all tasks must be assigned to a station to meet all the needs of precedence and minimizing the number of stations resulting n.

The ideal of balance occurs when the sum of execution times of tasks of each season coincides with the cycle time. In this case, the distribution of work stations has been perfectly balanced, there being no station and no bottleneck with idle time. But unequal execution times of tasks and the constraints imposed by the precedence makes this goal is virtually unattainable. However, perfect balance is a point of reference to be pursued: holding the balance with the smallest number of possible workstations. This concept is known as the theoretical minimum, MT, which is expressed as: MT = å t _i / c, where you run time of the task i and t _i å total execution time required to produce one unit of product. When MT is not an integer, must be adjusted for excess, as meaningless to speak of fractional workstations.

As shown below, if you get the number of stations, n where the chain is broken is minimized and MT match, it will automatically achieving three objectives:

Minimizing idle times: to

Maximize efficiency: E.

Minimize the delay balancing: R.

The idle time is the total downtime in the manufacture of a unit for the set of all workstations. Each of the n stations takes c seconds per unit, so that nc is the total time required per unit, including productive and unproductive time. If you subtract this total must obtain the required total all idle or unproductive time: to = nc – to you. Efficiency shall be expressed as the ratio by dividing the time required and the time required or used: E ( %) = 100 to you / nc. While the superior efficiency does not reach 100 to 100 there will be a delay balanced: R (%) = 100 – E.

.-. 2.4.3.3 Assigning tasks to workstations.

The number of possible solutions can be very high, increasing the number of stations and the number of tasks, being heuristic procedures are followed and provide, therefore, a satisfactory solution. The steps are:

a) Start with the first station to form, which is assigned the number 1.

It produces a list of all possible tasks that could be included in the station in question, which must satisfy three conditions:

Have not been assigned yet to any station.

All its preceding tasks had to be assigned to this or any previous season.

Their execution times, you can not exceed the station’s idle time, in this moment, is the difference between cycle time, c, and the sum of execution times of tasks that have already been assigned to the season that is forming.

c) is selected from among the candidates on the list, a task. For this selection is usually one of the following two rules:

Rule one: You select that task whose execution time is higher. Thus, they tend to allocate as soon as possible the most difficult to fit into the stations. Tasks with shorter t _i reserve for a more precise adjustment of the solution. In the example this rule.

Rule 2: Select this task to have a greater number of following tasks. This facilitates to keep more options open to form the subsequent seasons. However, the needs of precedence can leave only a few options of possible task sequences, resulting in a total downtime of excessive and unnecessary.

d) Calculate the cumulative time of all tasks assigned so far to the station in question and deducted the cycle time for idle time. Return to step b).

e) If there is any task assigned, but can not be the station that is being formed at that time, you must create a new station. This will be assigned a number equal to the previous season increased by one unit and return to step b). In the event that no other task is not to allocate the settlement will have been completed.

.-. 2.4.3.4 Evaluating the effectiveness and efficiency of the solution.

The solution will be effective if it reaches the desired capacity, which has sought to rely c wing of the desired output, and will be efficient if it minimizes the idle time. Both variables will be explored, taking into account that at times may be increased by deviations from the process outlined, for example, allocating more than one worker to specific seasons or making the same worker doing business in more than one station taking advantage of idle time.

EXAMPLE:. Balancing chains

A company will install an assembly to draw up one of their products. Knowing that the production required in a workday of eight hours is 600 units should be performed, balanced line, considering the tasks from highest to lowest runtime.

Definition of tasks and identification of precedence: the table shows the tasks that are part of the process and their execution times, ti, and their precedence relationships. The corresponding precedence graph is as follows:

L

B

G

H

D

F

E

C

A

J

I

K

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b) Calculation of minimum number of stations

The number of units produced per hour, r, should be: r = 600 / 8 = 75 a / hr. Hence the cycle time of the chain is: c = (1 / 75) 3600 = 48 sec / one. With this cycle time, the minimum number of workstations in which the chain can be subdivided shall be: MT = å t _i / c = 226/48 = 4.708 ~ 5.

If the balancing could be done with 5 workstations, the total downtime of the line would be: to = nc-åt _i = 5 x 48-226 = 240-226 = 14 sec., Efficiency would take the value E = 100 å t _i / nc = 100 x 226/240 = 94.17 for 100 and the delay of the balancing will be just 5.83%.

c) Allocation of tasks to stations.

The allocation of tasks to workstations in terms of the greatest times of their execution, taking into account the process indicated.

The chain has been balanced on the minimum number of workstations as possible, so that efficiency and achieve balanced delay previously calculated values.

2.4.4 .- Analysis for process plant layout.

The key decision taken in this case is the provision of workshops. In reaching this decision shall remain primarily the satisfaction of criteria such as reducing the distance covered and the cost of material handling (or, in the case of services, reduce customer trips) trying to boost the efficiency of operations . Thus, the surface and shape of the floor of the building, safety and hygiene at work, load limits, the fixed location of certain elements, etc.., Limit and probably modify the solutions obtained in a first approximation.

If there is a clearly dominant material flow distribution on the rest of the workshops could resemble the layout of equipment in a production line. However, this is not usual, having to resort to some criterion that determines the ordination. The factor that most often discussed but rarely is alone for the reasons already stated, the cost of handling and transport of materials between different workplaces. Of course, this depends on the movement of materials, but also of the necessity to have the staff to run those routes based on monitoring, inspection, working directly or simple communication. Since for a given product mentioned costs increase with the distances to travel, the relative distribution of the departments will affect that cost.

Analysis process consists generally of three phases:

• Collection of information.
• Development of a block plan
• Detailed design of the distribution.

2.4.4.1. Collection of information

First, you need to know the space requirements of each work area. This requires a prior calculation beginning with the demand forecasts, which in turn will translate into a production plan in an estimate of hours needed to produce such a plan and therefore the number of workers and machines necessary for workspaces. In this calculation will themselves be regarded as fluctuations in demand and production to which we referred earlier.

To calculate the total space requirements, we must take into consideration the following areas:

Static area (S _E): the physical space needed by the machines and jobs.

Surface gravity (S _G) for the workers to develop their work and the materials and tools can be positioned (S _G = S _E n, where n is the number of accessible side of the machine to work).

Surface evolution (Sv): enough space to allow tours of materials and workers (Sv = (S _G + S _E) k, where k is a coefficient which varies between 0.05 and 3, depending on the type of industry)

Total area required (S _T) of a department or section: S _T = S _E + S _G + Sv

As the space available, in principle enough to know what is the total area of the plant in a first approximation, grid and estimate the availability for each section.

2.4.4.2. Development of a block plan.

Once the size of the sections will be necessary to its management within the existing structure or to determine the desired form leading to the construction of the plant that has to encompass. The distribution phase has an extremely large number of possible solutions so that, in the vast majority of cases, leads to the determination of a solution that achieves the objectives set and met where possible restrictions, but without to determine the optimal solution.

Quantitative criteria: The cost of transport, it minimize the cost of movement of materials between sections.

Qualitative criteria: proximity priorities. Commonly applied technique is the SLP (Systematic Layout Planning).

6.4.4.3 .- Detailed breakdown.

The management of equipment and machines within each department, giving a detailed breakdown of the facilities and all its elements.

Bibliography:

Domínguez Machuca: Operations Management. Strategic issues in production and services.