What is Project Management?

A project is made up of a group of interrelated work activities constrained by a specific

scope, budget, and schedule to deliver capital assets needed to achieve the strategic

goals of an Agency. All projects must have a beginning and an end.

The management of construction projects requires knowledge of modern management as well as

an understanding of the design and construction process. Construction projects have a specific set

of objectives and constraints such as a required time frame for completion. While the relevant

technology, institutional arrangements or processes will differ, the management of such projects

has much in common with the management of similar types of projects in other specialty or

technology domains such as aerospace, pharmaceutical and energy developments.

Project management is the art of directing and coordinating human and material resources

throughout the life of a project by using modern management techniques to achieve predetermined

objectives of scope, cost, time, quality and participation satisfaction.

By contrast, the general management of business and industrial corporations assumes a broader

outlook with greater continuity of operations. Nevertheless, there are sufficient similarities as well

as differences between the two so that modern management techniques developed for general

management may be adapted for project management.

The basic ingredients for a project management framework may be represented schematically in

Figure 2-1. A working knowledge of general management and familiarity with the special

knowledge domain related to the project are indispensable. Supporting disciplines such as

computer science and decision science may also play an important role. In fact, modern

management practices and various special knowledge domains have absorbed various techniques

or tools which were once identified only with the supporting disciplines. For example, computer-

based information systems and decision support systems are now common-place tools for general

management. Similarly, many operations research techniques such as linear programming and

network analysis are now widely used in many knowledge or application domains. Hence, the

representation in Figure 2-1 reflects only the sources from which the project management

framework evolves.

Figure 2-1: Basic Ingredients in Project Management

Poject management in construction encompasses a set of objectives which may be accomplished

by implementing a series of operations subject to resource constraints. There are potential

conflicts between the stated objectives with regard to scope, cost, time and quality, and the

constraints imposed on human material and financial resources. These conflicts should be

resolved at the onset of a project by making the necessary tradeoffs or creating new alternatives.

Subsequently, the functions of project management for construction generally include the

following:

1. Specification of project objectives and plans including delineation of scope, budgeting,

scheduling, setting performance requirements, and selecting project participants.

2. Maximization of efficient resource utilization through procurement of labor, materials and

equipment according to the prescribed schedule and plan.

3. Implementation of various operations through proper coordination and control of planning,

design, estimating, contracting and construction in the entire process.

4. Development of effective communications and mechanisms for resolving conflicts among the

various participants.

The Project Management Institute focuses on nine distinct areas requiring project manager

knowledge and attention:

1. Project integration management to ensure that the various project elements are effectively

coordinated.

2. Project scope management to ensure that all the work required (and only the required work) is

included.

3. Project time management to provide an effective project schedule.

4. Project cost management to identify needed resources and maintain budget control.

5. Project quality management to ensure functional requirements are met.

6. Project human resource management to development and effectively employ project

personnel.

7. Project communications management to ensure effective internal and external

communications.

8. Project risk management to analyze and mitigate potential risks.

9. Project procurement management to obtain necessary resources from external sources.

Construction planning is a fundamental and challenging activity in the management and execution

of construction projects. It involves the choice of technology, the definition of work tasks, the

estimation of the required resources and durations for individual tasks, and the identification of

any interactions among the different work tasks. A good construction plan is the basis for

developing the budget and the schedule for work. Developing the construction plan is a critical

task in the management of construction, even if the plan is not written or otherwise formally

recorded. In addition to these technical aspects of construction planning, it may also be necessary

to make organizational decisions about the relationships between project participants and even

which organizations to include in a project. For example, the extent to which sub-contractors will

be used on a project is often determined during construction planning.

The Role of Project Managers:-

A project’s execution is planned and controlled by the project manager. The project

manager is assigned by the Agency, i.e., the Agency’s executive management. The

project manager must have adequate authority to exercise the responsibility of forming

and managing a team for support of the project. The project manager must have prior

experience managing similar projects in the past. If an Agency cannot commit such an

individual with adequate time and resources, the Agency is well advised to outsource

project management services for management of the project. The project manager may

be tasked with management of multiple projects that may require assignment of additional

project managers for support. In such cases the project manager is taking on the role of a program

manager.

activities without a project manager. It shows the multiple interactions an Agency faces without a

project manager to manage the work

activities involved in delivering a new capital asset.

project management organization is structured with the assignment of a project manager to

manage project work activities.

Major Types of Construction:-

1. Residential Housing Construction

2. Institutional and Commercial Building Construction

3. Specialized Industrial Construction

4. Infrastructure and Heavy Construction

Different methods of project management:-

1. Critical path method (CPM)

2. Program evaluation and review technique (PERT)

3. Lean construction method

4. Just in time method

5. Ant colony optimization

6. Monte Carlo method

7. Line of balance method (LOB)

Description of Methods

1.Critical path method (CPM):-

In 1957, DuPont developed a project management method designed to address the challenge of

shutting down chemical plants for maintenance and then restarting the plants once the

maintenance had been completed. Given the complexity of the process, they developed the

Critical Path Method (CPM) for managing such projects.

CPM provides the following benefits:

• Provides a graphical view of the project.

• Predicts the time required to complete the project.

• Shows which activities are critical to maintaining the schedule and which are not.

CPM models the activities and events of a project as a network. Activities are depicted as nodes

on the network and events that signify the beginning or ending of activities are depicted as arcs or

lines between the nodes. The following is an example of a CPM network diagram:

CPM Diagram

Steps in CPM Project Planning

1. Specify the individual activities.

2. Determine the sequence of those activities.

3. Draw a network diagram.

4. Estimate the completion time for each activity.

5. Identify the critical path (longest path through the network)

6. Update the CPM diagram as the project progresses.

1. Specify the Individual Activities

From the work breakdown structure, a listing can be made of all the activities in the project. This

listing can be used as the basis for adding sequence and duration information in later steps.

2. Determine the Sequence of the Activities

Some activities are dependent on the completion of others. A listing of the immediate

predecessors of each activity is useful for constructing the CPM network diagram.

3. Draw the Network Diagram

Once the activities and their sequencing have been defined, the CPM diagram can be drawn. CPM

originally was developed as an activity on node (AON) network, but some project planners prefer

to specify the activities on the arcs.

4. Estimate Activity Completion Time

The time required to complete each activity can be estimated using past experience or the

estimates of knowledgeable persons. CPM is a deterministic model that does not take into account

variation in the completion time, so only one number is used for an activity's time estimate.

5. Identify the Critical Path

The critical path is the longest-duration path through the network. The significance of the critical

path is that the activities that lie on it cannot be delayed without delaying the project. Because of

its impact on the entire project, critical path analysis is an important aspect of project planning.

The critical path can be identified by determining the following four parameters for each activity:

• ES - earliest start time: the earliest time at which the activity can start given that its precedent

activities must be completed first.

• EF - earliest finish time, equal to the earliest start time for the activity plus the time required

to complete the activity.

• LF - latest finish time: the latest time at which the activity can be completed without delaying

the project.

• LS - latest start time, equal to the latest finish time minus the time required to complete the

activity.

The slack time for an activity is the time between its earliest and latest start time, or between its

earliest and latest finish time. Slack is the amount of time that an activity can be delayed past its

earliest start or earliest finish without delaying the project.

The critical path is the path through the project network in which none of the activities have slack,

that is, the path for which ES=LS and EF=LF for all activities in the path. A delay in the critical

path delays the project. Similarly, to accelerate the project it is necessary to reduce the total time

required for the activities in the critical path.

6. Update CPM Diagram

As the project progresses, the actual task completion times will be known and the network

diagram can be updated to include this information. A new critical path may emerge, and

structural changes may be made in the network if project requirements change.

CPM Limitations

CPM was developed for complex but fairly routine projects with minimal uncertainty in the

project completion times. For less routine projects there is more uncertainty in the completion

times, and this uncertainty limits the usefulness of the deterministic CPM model. An alternative to

CPM is the PERT project planning model, which allows a range of durations to be specified for

each activity.

2.Program evaluation and review technique (PERT):-

Complex projects require a series of activities, some of which must be performed sequentially and

others that can be performed in parallel with other activities. This collection of series and parallel

tasks can be modeled as a network.

In 1957 the Critical Path Method (CPM) was developed as a network model for project

management. CPM is a deterministic method that uses a fixed time estimate for each activity.

While CPM is easy to understand and use, it does not consider the time variations that can have a

great impact on the completion time of a complex project.

The Program Evaluation and Review Technique (PERT) is a network model that allows for

randomness in activity completion times. PERT was developed in the late 1950's for the U.S.

Navy's Polaris project having thousands of contractors. It has the potential to reduce both the time

and cost required to complete a project.

The Network Diagram

In a project, an activity is a task that must be performed and an event is a milestone marking the

completion of one or more activities. Before an activity can begin, all of its predecessor activities

must be completed. Project network models represent activities and milestones by arcs and nodes.

PERT originally was an activity on arc network, in which the activities are represented on the

lines and milestones on the nodes. Over time, some people began to use PERT as an activity on

node network. For this discussion, we will use the original form of activity on arc.

The PERT chart may have multiple pages with many sub-tasks. The following is a very simple

example of a PERT diagram:

PERT Chart

The milestones generally are numbered so that the ending node of an activity has a higher number

than the beginning node. Incrementing the numbers by 10 allows for new ones to be inserted

without modifying the numbering of the entire diagram. The activities in the above diagram are

labeled with letters along with the expected time required to complete the activity.

Steps in the PERT Planning Process

PERT planning involves the following steps:

1. Identify the specific activities and milestones.

2. Determine the proper sequence of the activities.

3. Construct a network diagram.

4. Estimate the time required for each activity.

5. Determine the critical path.

6. Update the PERT chart as the project progresses.

1. Identify Activities and Milestones

The activities are the tasks required to complete the project. The milestones are the events

marking the beginning and end of one or more activities. It is helpful to list the tasks in a table that

in later steps can be expanded to include information on sequence and duration.

2. Determine Activity Sequence

This step may be combined with the activity identification step since the activity sequence is

evident for some tasks. Other tasks may require more analysis to determine the exact order in

which they must be performed.

3. Construct the Network Diagram

Using the activity sequence information, a network diagram can be drawn showing the sequence

of the serial and parallel activities. For the original activity-on-arc model, the activities are

depicted by arrowed lines and milestones are depicted by circles or "bubbles".

If done manually, several drafts may be required to correctly portray the relationships among

activities. Software packages simplify this step by automatically converting tabular activity

information into a network diagram.

4. Estimate Activity Times

Weeks are a commonly used unit of time for activity completion, but any consistent unit of time

can be used.

A distinguishing feature of PERT is its ability to deal with uncertainty in activity completion

times. For each activity, the model usually includes three time estimates:

• Optimistic time - generally the shortest time in which the activity can be completed. It is

common practice to specify optimistic times to be three standard deviations from the mean so

that there is approximately a 1% chance that the activity will be completed within the

optimistic time.

• Most likely time - the completion time having the highest probability. Note that this time is

different from the expected time.

• Pessimistic time - the longest time that an activity might require. Three standard deviations

from the mean is commonly used for the pessimistic time.

PERT assumes a beta probability distribution for the time estimates. For a beta distribution, the

expected time for each activity can be approximated using the following weighted average:

Expected time = ( Optimistic + 4 x Most likely + Pessimistic ) / 6

This expected time may be displayed on the network diagram.

To calculate the variance for each activity completion time, if three standard deviation times were

selected for the optimistic and pessimistic times, then there are six standard deviations between

them, so the variance is given by:

[ ( Pessimistic - Optimistic ) / 6 ]2

5. Determine the Critical Path

The critical path is determined by adding the times for the activities in each sequence and

determining the longest path in the project. The critical path determines the total calendar time

required for the project. If activities outside the critical path speed up or slow down (within

limits), the total project time does not change. The amount of time that a non-critical path activity

can be delayed without delaying the project is referred to as slack time.

If the critical path is not immediately obvious, it may be helpful to determine the following four

quantities for each activity:

• ES - Earliest Start time

• EF - Earliest Finish time

• LS - Latest Start time

• LF - Latest Finish time

These times are calculated using the expected time for the relevant activities. The earliest start and

finish times of each activity are determined by working forward through the network and

determining the earliest time at which an activity can start and finish considering its predecessor

activities. The latest start and finish times are the latest times that an activity can start and finish

without delaying the project. LS and LF are found by working backward through the network. The

difference in the latest and earliest finish of each activity is that activity's slack. The critical path

then is the path through the network in which none of the activities have slack.

The variance in the project completion time can be calculated by summing the variances in the

completion times of the activities in the critical path. Given this variance, one can calculate the

probability that the project will be completed by a certain date assuming a normal probability

distribution for the critical path. The normal distribution assumption holds if the number of

activities in the path is large enough for the central limit theorem to be applied.

Make adjustments in the PERT chart as the project progresses. As the project unfolds, the

estimated times can be replaced with actual times. In cases where there are delays, additional

resources may be needed to stay on schedule and the PERT chart may be modified to reflect the

new situation.

Benefits of PERT

PERT is useful because it provides the following information:

• Expected project completion time.

• Probability of completion before a specified date.

• The critical path activities that directly impact the completion time.

• The activities that have slack time and that can lend resources to critical path activities.

• Activity start and end dates.

Limitations

The following are some of PERT's weaknesses:

• The activity time estimates are somewhat subjective and depend on judgement. In cases where

there is little experience in performing an activity, the numbers may be only a guess. In other

cases, if the person or group performing the activity estimates the time there may be bias in

the estimate.

• Even if the activity times are well-estimated, PERT assumes a beta distribution for these time

estimates, but the actual distribution may be different.

• Even if the beta distribution assumption holds, PERT assumes that the probability distribution

of the project completion time is the same as the that of the critical path. Because other paths

can become the critical path if their associated activities are delayed, PERT consistently

underestimates the expected project completion time.

The underestimation of the project completion time due to alternate paths becoming critical is

perhaps the most serious of these issues. To overcome this limitation, Monte Carlo simulations

can be performed on the network to eliminate this optimistic bias in the expected project

completion time.

3. Lean construction method

Managing construction under Lean is different from typical contemporary practice

because it;

��has a clear set of objectives for the delivery process,

��is aimed at maximizing performance for the customer at the project level,

��designs concurrently product and process, and

��applies production control throughout the life of the project.

By contrast, the current form of production management in construction is derived from the

same activity centered approach found in mass production and project management. It aims

to optimize the project activity by activity, assuming customer value has been identified in

design. Production is managed throughout a project by first breaking the project into pieces,

i.e. design and construction, then putting those pieces in a logical sequence, estimating the

time and resources required to complete each activity and therefore the project. Each piece or

activity is further decomposed until it is contracted out or assigned to a task leader, foreman

or squad boss. Control is conceived as monitoring each contract or activity against its

schedule and budget projections. These projections are rolled up to project level reports. If

Reliable workflow was a consequence of stopping the line rather than a stated objective.

activities or chains along the critical path fall behind, efforts are made to reduce cost and

duration of the offending activity or changing the sequence of work. If these steps do not

solve the problem, it is often necessary to trade cost for schedule by working out of the best

sequence to make progress. The focus on activities conceals the waste generated between

continuing activities by the unpredictable release of work and the arrival of needed resources.

Simply put, current forms of production and project management focus on activities and

ignore flow and value considerations (Koskela 1992, Koskela and Huovila 1997).

Managing the combined effect of dependence and variation is a first concern in lean

production. Goldratt (1986) illustrates the effects on production in “The Goal” and the

application to construction is demonstrated by Tommelein et al. (1999) in “Parade of Trades.

The problem of dependence and variation can be illustrated by what happens in heavy traffic

on a freeway. If every car drove at exactly the same speed then spacing between cars could

be very small and the capacity of the freeway would be limited by whatever speed was set.

Each car would be dependent on the one ahead to release pavement and variation would be

zero. In effect, there would be no inventory of unused pavement. In reality of course, each

car does use the pavement released to it from the car ahead but speeds vary.

Under the pressure to get to work or home, gaps between cars close and any variation in

speed demands immediate response from following cars. As the gaps close, small variations

in speed propagate along and across lanes. One small hesitation can lead to a huge standing

wave as traffic slows to a crawl. Recovery is difficult because it is impossible to get everyone

to accelerate smoothly back up to the standard speed and interval. High speed at any one

moment does not assure minimum travel time in conditions of dependence and variation. The

idea that you do not get home any faster by driving as fast and as close to the car ahead is

counter intuitive (at least to teenagers). Certainly the system itself does not function as well

when dependence is tighter and variation greater.

Managing the interaction between activities, the combined effects of dependence and

variation, is essential if we are to deliver projects in the shortest time. Minimizing the

combined effects of dependence and variation becomes a central issue for the planning and

control system as project duration is reduced and the complexity increases. (Complexity is

defined by the number of pieces or activities that can interact.) The need to improve

reliability in complex and quick circumstances is obvious. New forms of planning and

control are required.

The first goal of lean construction must be to fully understand the underlying “physics”

of production, the effects of dependence and variation along supply and assembly chains.

These physical issues are ignored in current practice which tend to focus on teamwork,

communication and commercial contracts. These more human issues are at the top of

practitioner’s lists of concerns because they do not, indeed cannot see the source of their

problems. It is not that these people are stupid, but that they lack the language and conceptual

foundation to understand the problem in physical production terms. The development of

partnering illustrates this point.

Partnering makes great sense from an activity perspective. But few realize Partnering is a

solution to the failure of central control to manage production in conditions of high

uncertainty and complexity. In these circumstances, representatives of each activity (or

contract) must be able to communicate directly with out relying on the central authority tol

control message flow, and so Partnering works. From the lean understanding of the physics

of production, Partnering is evidence of a failure in production management but it provides

the opportunity for collaborative redesign of the planning system to support close

coordination and reliable work flow.

Lean supports the development of team work and a willingness to shift burdens along

supply chains. Partnering relationships coupled with lean thinking make rapid

implementation possible. Where Partnering is about building trust, lean is about building

reliability. Trust is the human attitude that arises in conditions of reliability. We are not likely

to trust one another very long if we do not demonstrate reliability. Reliability is the result of

the way systems are designed. Of course people manage systems and in current terms they do

a fine job. The problem is that production systems just do not work well when every person

tries to optimize their performance without understanding how their actions affect the larger

web.

The problem of matching labor to available work offers a good example of the difference

between the contemporary view of the workplace and lean. “Matching labor to work” means

having the resources on hand for a crew to work steadily and without interruption. Current

practice views the assignment to the crew as a sort of “mini contract” which is more or less

independent of other assignments, and sets the person in charge responsible for the

organization of resources and direction of the crew. To be fair, companies have logistics

systems that try to get the resources close to the crew and a few actually try to assemble and

assign packages of work. But the majority of foremen are responsible for the final collection

of resources and assuring that their crews can work continuously. When this approach fails to

produce acceptable results, when the numbers are bad, management assumes the foreman or

crew is not performing.

Companies typically maintain elaborate cost control systems to measure this

performance. These systems are the manifestations of the cause and effect theories operating

in the company. At the heart of this model is the belief that the crew is essentially

independent and that all costs charged to an account arise within from the effort necessary to

complete the assignment by the crew.

The lean construction view is different as it views the problem in physical production

terms. The crew works at variable rates using resources supplied at varying rates. Matching

labor to available work is a difficult systems design problem with a limited number of

“solutions.” Lean works to isolate the crew from variation in supply by providing an

adequate backlog (a safe distance between cars) or tries to maintain excess capacity in the

crew so they can speed up or slow as conditions dictate. On occasion, people acting on

intuition apply these techniques. (They drive to work on freeways.) Unfortunately neither

resource nor capacity buffers reduce the variation in supply and use rates of downstream

crews.

These problems are solved by long and predictable runs in the factories (and along the

highways of our dreams). In these stable circumstances managers can predict the work

content at each station and shift labor along the line to minimize imbalance. Such factories

are mostly dreams that have little to do with construction where we only have some idea of

the labor content of activities from previous projects.

People holding current practice dear sometimes say they are helpless victims of fate when

faced with managing uncertainty on projects. Their view is that uncertainty arises in other

activities beyond their control. The lean approach is to assure we do not contribute to

variation in work flow and to decouple when we cannot get it under control. In lean

construction as in much of manufacturing, planning and control are two sides of a coin that

keeps revolving throughout a project.

��Planning: defining criteria for success and producing strategies for achieving

objectives.

��Control: causing events to conform to plan and triggering learning and replanning.

Often the first question we are asked when describing a project to people unfamiliar with

lean thinking is, “What kind of contract was in force?” Next come organizational and

systems issues: “Was supervision by area or craft? Union or not? Were designers on site?

Did the owner know what they wanted?” These questions are reflections of contracting or

activity centered thinking. Lean construction rests on a production management mind. We

ask about the way work itself is planned and managed. We want to know the whether the

planning system itself is under control, the location of inventories and excess capacity, and

the extent to which the design and construction process itself supports customer value.

Lean construction embraces uncertainty in supply and use rates as the first great

opportunity and employ production planning to make the release of work to the next crew

more predictable, and then we work within the crews to understand the causes of variation.

4. Just in time method

1.0 Introduction

The acronym JIT has been highly visible since the late 1980's, as

manufacturing attempted to meet competitive challenges by adopting

newly emerging management theories and techniques. What is JIT?

Manufacturing JIT is a method of pulling work forward from one

process to the next "just-in-time"; i.e. when the successor process needs it,

ultimately producing throughput. One benefit of manufacturing JIT is

reducing work-in-process inventory, and thus working capital. An even

greater benefit is reducing production cycle times, since materials spend

less time sitting in queues waiting to be processed. However, the greatest

benefit of manufacturing JIT is forcing reduction in flow variation, thus

contributing to continuous, ongoing improvement. Can this approach be

applied to construction? What is "Construction JIT"?

Construction JIT vs Manufacturing JIT

JIT is a technique developed by Taichi Ohno and his fellow workers

at Toyota . Ohno's fundamental purpose was to change production's

directives from estimates of demand to actual demand--a purpose

originally rooted in the absence of a mass market and the need to

produce small lots of many product varieties.

In assembly line production systems managed by lean production

concepts, the directives for production are provided by means of kanban

from downstream processes. This system insures that whatever is

produced is throughput, i.e. is needed for the production of an order.

Kanban works as a near-term adjusting mechanism within a system of

production scheduling that strives for firm and stable aggregate output

quantities, and provides all suppliers in the extended process

progressively more specific production targets as the plan period

approaches, resulting ultimately in a firm 2-6 week production schedule.

This system provides sufficient flexibility to adjust to actual demand,

while assuring that all resources are applied to the production of

throughput.

In manufacturing, the need for flexibility comes from a potential

difference between forecast and actual demand. Many products are being

produced, so it is important to minimize the time required to produce any

specific type of product demanded. In construction, there is only one

product produced once. And in the case of industrial construction, that

product is the facility for producing manufacturing's products. It is

consequently important to reduce the time needed to produce the facility,

not necessarily the time to produce any component. (NB: This fact often

conflicts with the different interests of the various organizations involved

in a project.) Further, changes arise from progressive definition of

customer wants, so flexibility is needed in order to respond to latebreaking

changes.

The application of JIT to construction differs substantially from its

application to manufacturing because construction and manufacturing

are different types of production, and because of the greater complexity

and uncertainty of construction.

The extent and significance of uncertainty in construction has been

adequately addressed in earlier papers but a moment's reflection

supports the view that construction is complex. The number of parts,

relative lack of standardization, and the multiple participants and

constraining factors easily make the construction of an automobile

factory more difficult than the production of an automobile in that

factory. When this complexity is joined with economic pressures to

minimize time and cost, that uncertainty results is not surprising. But is

construction really a different type of production than manufacturing, or

simply a more complex and uncertain version of manufacturing itself?

What kind of production is construction?

Construction is the final component in manufacturing's product

development process. Construction is complete before manufacturing's

production begins. Consequently, it is misleading to conceive construction

as analogous to factory production (although some aspects of

construction fit better in that analogy; i.e. fabrication). Construction is

best conceived as a product development process, extending from product

design through process design to facility (the manufacturing process tool)

construction, the end result of which is readiness for manufacturing.

Admittedly, this is a best fit in the case of industrial construction,

and becomes less plausible as we move toward the cookie cutter end of

the industry spectrum, e.g. manufactured housing. There seems to be a

gray zone between manufacturing and construction, where the work looks

like construction because final assembly is done where the facility is to be

used, but looks like manufacturing because all that remains of the process

is to match production output with sales. This gray zone is obviously ripe

for industrialization and mechanization, which ultimately pushes it over

into the camp of manufacturing. The proper business of construction is

completing product and process design. Once that is done, it is but a

matter of time before wit and invention capture mere assembly for

manufacturing.

Uncertainty is a necessary component in construction conceived as a

product development process. The very purpose of the process is to

surface and resolve trade-offs between means and ends, all the way from

product design through facility construction. The management of projects

so conceived is the proper terrain for lean construction concepts and

techniques. So, construction is a different type of production than

manufacturing, and has greater uncertainty and flow variation. Is there

an application for JIT in construction?

Using JIT to reduce variation and waste: Manufacturing vs

Construction

By minimizing inventories between processes, Ohno removed the

safety stock that allowed a downstream process to continue working when

a feeder process failed. He also required that operators stop the

production line when they were unable to fix problems.

5. Ant colony optimization

The ant colony optimization algorithm (ACO), is a probabilistic technique for solving

computational problems which can be reduced to finding good paths through graphs.

This algorithm is a member of ant colony algorithms family, in swarm intelligence methods, and

it constitutes some met heuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his

PhD thesis [1]

[2]

, the first algorithm was aiming to search for an optimal path in a graph; based on

the behavior of ants seeking a path between their colony and a source of food. The original idea

has since diversified to solve a wider class of Numerical problems, and as a result, several

problems have emerged, drawing on various aspects of the behavior of ants

In the real world, ants (initially) wander randomly, and upon finding food return to their colony

while laying down pheromone trails. If other ants find such a path, they are likely not to keep

travelling at random, but to instead follow the trail, returning and reinforcing it if they eventually

find food (see Ant communication).

Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength.

The more time it takes for an ant to travel down the path and back again, the more time the

pheromones have to evaporate. A short path, by comparison, gets marched over faster, and thus

the pheromone density remains high as it is laid on the path as fast as it can evaporate. Pheromone

evaporation has also the advantage of avoiding the convergence to a locally optimal solution. If

there were no evaporation at all, the paths chosen by the first ants would tend to be excessively

attractive to the following ones. In that case, the exploration of the solution space would be

constrained.

Thus, when one ant finds a good (i.e., short) path from the colony to a food source, other ants are

more likely to follow that path, and positive feedback eventually leads all the ants following a

single path. The idea of the ant colony algorithm is to mimic this behavior with "simulated ants"

walking around the graph representing the problem to solve.

Detailed

The original idea comes from observing the exploitation of food resources among ants, in which

ants’ individually limited cognitive abilities have collectively been able to find the shortest path

between a food source and the nest.

1. The first ant finds the food source (F), via any way (a), then returns to the nest (N), leaving

behind a trail pheromone (b)

2. Ants indiscriminately follow four possible ways, but the strengthening of the runway makes it

more attractive as the shortest route.

3. Ants take the shortest route, long portions of other ways lose their trail pheromones.

In a series of experiments on a colony of ants with a choice between two unequal length paths

leading to a source of food, biologists have observed that ants tended to use the shortest route. [3]

[4]

A model explaining this behaviour is as follows:

1. An ant (called "blitz") runs more or less at random around the colony;

2. If it discovers a food source, it returns more or less directly to the nest, leaving in its path a

trail of pheromone;

3. These pheromones are attractive, nearby ants will be inclined to follow, more or less directly,

the track;

4. Returning to the colony, these ants will strengthen the route;

5. If two routes are possible to reach the same food source, the shorter one will be, in the same

time, traveled by more ants than the long route will

6. The short route will be increasingly enhanced, and therefore become more attractive;

7. The long route will eventually disappear, pheromones are volatile;

8. Eventually, all the ants have determined and therefore "chosen" the shortest route.

Ants use the environment as a medium of communication. They exchange information indirectly

by depositing pheromones, all detailing the status of their "work". The information exchanged has

a local scope, only an ant located where the pheromones were left has a notion of them. This

system is called "Stemberg" and occurs in many social animal societies (it has been studied in the

case of the construction of pillars in the nests of termites). The mechanism to solve a problem too

complex to be addressed by single ants is a good example of a self-organized system. This system

is based on positive feedback (the deposit of pheromone attracts other ants that will strengthen it

themselves) and negative (dissipation of the route by evaporation prevents the system from

thrashing). Theoretically, if the quantity of pheromone remained the same over time on all edges,

no route would be chosen. However, because of feedback, a slight variation on an edge will be

amplified and thus allow the choice of an edge. The algorithm will move from an unstable state in

which no edge is stronger than another, to a stable state where the route is composed of the

strongest edges.

Application

Ant colony optimization algorithms have been applied to many combinatorial optimization

problems, ranging from quadratic assignment to fold protein or routing vehicles and a lot of

derived methods have been adapted to dynamic problems in real variables, stochastic problems,

multi-targets and parallel implementations. It has also been used to produce near-optimal solutions

to the travelling salesman problem. They have an advantage over simulated annealing and genetic

algorithm approaches of similar problems when the graph may change dynamically; the ant

colony algorithm can be run continuously and adapt to changes in real time. This is of interest in

network routing and urban transportation systems.

As a very good example, ant colony optimization algorithms have been used to produce near-

optimal solutions to the travelling salesman problem. The first ACO algorithm was called the Ant

system [5]

and it was aimed to solve the travelling salesman problem, in which the goal is to find

the shortest round-trip to link a series of cities. The general algorithm is relatively simple and

based on a set of ants, each making one of the possible round-trips along the cities. At each stage,

the ant chooses to move from one city to another according to some rules:

1. It must visit each city exactly once;

2. A distant city has less chance of being chosen (the visibility);

3. The more intense the pheromone trail laid out on an edge between two cities, the greater the

probability that that edge will be chosen;

4. Having completed its journey, the ant deposits more pheromones on all edges it traversed, if

the journey is short;

5. After each iteration, trails of pheromones evaporate

.

6. Monte Carlo method

What is Monte Carlo Simulation?

Monte Carlo simulation, or probability simulation, is a technique used to understand the impact of

riskand uncertainty in financial, project management, cost, and other forecasting models.

How It Works

In a Monte Carlo simulation, a random value is selected for each of the tasks, based on the range

of estimates. The model is calculated based on this random value. The result of the model is

recorded, and the process is repeated. A typical Monte Carlo simulation calculates the model

hundreds or thousands of times, each time using different randomly-selected values.

When the simulation is complete, we have a large number of results from the model, each based

on

random input values. These results are used to describe the likelihood, or probability, of reaching

various results in the model.

For Example

For example, consider the model described above: we are estimating the total time it will take to

complete a particular project. In this case, it's a construction project, with three parts. The parts

have

to be done one after the other, so the total time for the project will be the sum of the three parts.

All the times are in months.

Task Time Estimate

Job 1 5 Months

Job 2 4 Months

Job 3 5 Months

Total 14 Months

Table 1: Basic Forecasting Model

In the simplest case, we create a single estimate for each of the three parts of the project. This

model gives us a result for the total time: 14 months. But this value is based on three estimates,

each of which is an unknown value. It might be a good estimate, but this model can't tell us

anything about risk.

How likely is it that the project will be completed on time?

To create a model we can use in a Monte Carlo simulation, we create three estimates for each part

of the project. For each task, we estimate the minimum and maximum expected time (based on

our

experience, or expertise, or historical information). We use these with the “most likely” estimate,

the

one that we used above:

Task Minimum Most Likely Maximum

Job 1 4 Months 5 Months 7 Months

Job 2 3 Months 4 Months 6 Months

Job 3 4 Months 5 Months 6 Months

Total 11 Months 14 Months 19 Months

Table 2: Forecasting Model Using Range Estimates

What is Monte Carlo Simulation?

This model contains a bit more information. Now there is a range of possible outcomes. The

project

might be completed in as little as 11 months, or as long as 19 months.

In the Monte Carlo simulation, we will randomly generate values for each of the tasks, then

calculate the total time to completion1. The simulation will be run 500 times. Based on the results

of the simulation, we will be able to describe some of the characteristics of the risk in the model.

To test the likelihood of a particular result, we count how many times the model returned that

result in the simulation. In this case, we want to know how many times the result was less than or

equal to a particular number of months.

Time Number of Times (Out of 500) Percent of Total (Rounded)

12 Months 1 0%

13 Months 31 6%

14 Months 171 34%

15 Months 394 79%

16 Months 482 96%

17 Months 499 100%

18 Months 500 100%

Table 3: Results of a Monte Carlo Simulation

The original estimate for the “most likely”, or expected case, was 14 months. From the Monte

Carlo

simulation, however, we can see that out of 500 trials using random values, the total time was 14

months or less in only 34% of the cases.

Put another way, in the simulation there is only a 34% chance – about 1 out of 3 – that any

individual trial will result in a total time of 14 months or less. On the other hand, there is a 79%

chance that the project will be completed within 15 months. Further, the model demonstrates that

it is extremely unlikely, in the simulation, that we will ever fall at the absolute minimum or

maximum total values.

This demonstrates the risk in the model. Based on this information, we might make different

choices

when planning the project. In construction, for example, this information might have an impact on

our financing, insurance, permits, and hiring needs. Having more information about risk at the

beginning means we can make a better plan for going forward.

7. Detailed description of Line of balance method (LOB):-

The Line of Balance (otherwise known as ‘Time-Distance’ or ‘Time-Chainage’) diagram is a

graphical technique particularly suited for projects that comprise multiple and similar units, such

as residential housing. The x-axis represents time and the y-axis the number of units (or similarly

may represent the extent of the work site). Sloping lines represent the activities of the project,

the gradient of the line indicating the rate of production.i

A Line of Balance (LOB) chart does not show direct relationships between individual activities; it

shows an output relationship between different operations in that one operation must be

completed at a particular rate for the subsequent relationship to proceed at the required rate.

Maintaining the theme of house building, the following graphic illustrates a LOB chart for a few

simple house construction activities:

Simple Line of Balance diagram illustrating house constructionii

The Gantt chart is a popular type of bar chart that illustrates a project schedule. Gantt charts

illustrate the start and finish dates of the activities and summary elements of a project. Activities

and summary elements comprise the work breakdown structure of the project. Some Gantt

charts also show the dependency (i.e. precedence network) relationships between activities.iii

A simple example of a Gantt chart based on the same example as used for the Line of Balance

definition is shown below:

Gantt chart showing simple house construction projectiv

The Development of the Two Separate Methods

The Line of Balance (LOB) technique was originated by the Goodyear Company in the early

1940's and was developed by the U.S. Navy in the early 1950's for the programming and control

of both repetitive and non-repetitive projects. LOB was first applied to industrial manufacturing

and production control, where the objective was to attain or evaluate a production line flow rate

of finished products.

The basic concepts of LOB have since been applied in the construction industry as a planning

and scheduling method. Several attempts either to modify the basic LOB technique or to

develop variations named differently have also been made (Examples, to name a few include:

velocity diagrams, the construction planning technique, the vertical production method, the

linear scheduling method, time space scheduling method, and repetitive project model)v.

Henry Laurence Gantt (1861-1919) was a mechanical engineer, industry advisor and

management consultant. He developed first examples of Gantt charts in 1910. Gantt charts were

used as a visual tool to illustrate the start and finish dates of the terminal elements and summary

elements of a project. Accepted as a commonplace project management tool today, it was an

innovation of world-wide importance at that time. Gantt charts were used in large construction

projects like the Hoover Dam started in 1931, and the USA interstate highway system started in

1956.vi

In the 1980s, personal computers eased the creation and editing of elaborate Gantt charts, and

they have since been developed from simple linked bar charts into network (or precedence)

diagrams and are widely used for planning and scheduling projects.

The Current Application of these Methods:-

Today, the Gantt chart is accepted as a commonplace project management tool. This method,

via the numerous desktop computer applications that are available, is primarily used by project

managers and project planners in the management of projects.

It is popular because it allows you to estimate how long a project should take, lays out the order

in which tasks need to be carried out, helps manage dependencies between tasks, determines the

resources needed, monitors progress and helps to see how remedial action may bring the project

back on course. You can also immediately see what should be done at some point in time. All

this is done through the assistance of the software packages whose analysis is based on network

analysis and illustrated by way of the Gantt chart.

LOB has not been fully developed and implemented by the construction industry because of the

immense popularity of network techniques including Critical Path Methods. Even though the

development of LOB predates the other techniques, the development of these other techniques

has overtaken it and it would seem that LOB is only used for specific types of projects such as

the resource scheduling and coordination of subcontractors, highway pavement construction

projects, modelling production activities for multi-facility projects, pipeline and transportation

projects.

A typical project is a housing project consisting of several houses where the same type of work

such as foundations, brickwork, roof construction, and internal trades are undertaken on each

house.

The Benefits of the Line of Balance Method:-

Network analysis methods are very popular in larger projects but present complications in

projects of repetitive nature such as high-rise building construction. Critical Path Method (CPM)

based techniques have been criticized for their inability to model repetitive projects. The first

problem is the sheer size of the network. In repetitive projects of n units, the network prepared

for one unit has to be repeated n times and linked to each other; this results in a huge network

that is difficult to manage. This may cause difficulties in communication among the members of

the construction management team and difficulties in foreseeing the likely effect of delays. The

second problem is that the Critical Path Method of analysis used in network analysis is designed

primarily for optimizing project duration rather than adequately dealing with the special resource

constraints of repetitive projects. Indeed, the critical path method has no capability to assure a

smooth procession of labour teams from unit to unit with no conflict and no idle time for

workers and equipment. This leads to hiring and procurement problems in the flow of labour

and material during construction.vii

The Line of Balance (LOB) method of scheduling is well suited to projects that are composed of

activities of a linear and repetitive nature. The major benefits of this method are that it provides

production rate and duration information in the form of an easily interpreted graphics format

and that it allows a smooth and efficient flow of resources.

Thus, it is clear that the LOB method allows a better grasp of a project composed of repetitive

activities than any other scheduling technique, because it allows the possibility to adjust the rate

of production of activities. The diagram can be progressed by plotting on the chart the work

achieved. This will then show at a glance what is wrong with the progress of an activity, and can

detect potential future bottlenecks. If the rate at which the work is being achieved is lower than

required, adjustments can be made to increase the output.

An example of this is illustrated below, using the house construction chart illustrated earlier. The

chart has now been updated to week 12 of the project. It can be seen that the ‘Foundations’ output

has fluctuated but that they are generally on schedule and almost complete. The ‘Brickwork’ and

‘Roof Construction’ are both though running behind schedule and the ‘Internal Works’ have not

started. By extrapolation though it can be seen that the first unit will be completed over 3 weeks

late. The overall project delay could also be determined by extrapolation, and using the same

house building example it can be determined that it would result in an overall delay of over 10

weeks.

Progressed Line of Balance diagram illustrating how the effect of lower

productivity has the potential to delay the house constructionviii

The above LOB method diagram illustrates clearly the activities that are running late. This

diagram can then be used as a project management tool to assess ways to mitigate the delay. The

mitigation would generally be in the form of increasing the output of the activity (either in the

form of increasing the efficiency or by increasing the resource employed on the activity) and

would be observed on the LOB diagram as an increase in the gradient of the activity line.

Using the house building project above as an example, by increasing the output for the

‘Brickwork’ and ‘Roof Construction’ the current observed output deficit can be minimised with

the

effect of reducing the overall delay. The amount of delay reduction relies on the improvement of

the activity output.

The essence of the LOB document is therefore one of output and productivity. In this respect

the document can have use in the process of claims for delay and/or disruption. If the LOB

document is produced contemporaneously it can identify any areas of low output or delay by

other causes thus enabling the circumstances to be addressed at the time. The chart thus

becomes a good illustration of any genuine claim for delay and/or disruption.

Finally, the LOB method requires less time and effort to produce than network schedules, and

can be generated on software as simple as Microsoft word and excel or can be prepared slickly

and efficiently using proprietary software.

The Down Side of Line of Balance:-

Line of Balance diagrams are not well suited to individual activities that have a short duration

and that are undertaken in isolation to similar activities in a project.

The method, and hence the diagram, also becomes more difficult and complex when dealing

with large construction projects consisting of a large number of inter-related activities. In these

situations the diagram may only be effective if illustrating summaries of groups of activities and

hence can only be effective as an over-view document; whereas a Gantt chart allows an

assessment as to how long a project should take, lays out the order in which tasks need to be

carried out and helps manage the dependencies between tasks.ix

A LOB diagram on the other hand does not show exact relationships between individual

activities in the same way as a Gantt chart does, and hence it is not easy to demonstrate a critical

path through the works. For more complex projects this would become impossible except at a

summarised over-view level.

For this reason Gantt charts tend to be the favoured option by Clients, and it is unlikely at

present for a LOB diagram to be accepted by Clients as either a Tender or a Contract

Programme.

CAN LINE OF BALANCE PROGRAMMES SUPERSEDE GANTT CHARTS INTHE

CONSTRUCTION INDUSTRY?

Both the Gantt chart and the Line of Balance diagram are techniques used in the construction

industry to illustrate the planned sequence of work and to allow adjustments due to changed

circumstances. The Gantt chart is the most widely used of the techniques; perceived by the

Construction Industry as being the easiest and most recognisable form of programming. The

Line of Balance method is less known and tends to be used on projects where there is a high

degree of repetitive work.

This article explains the different methods, what they look like and reviews the pros and cons of

each. It also investigates whether the Line of Balance method could ever supersede the Gantt

Chart method.

Conclusion:-

There are potentially very few projects where a LOB diagram cannot be used and be of benefit.

As seen above though, for more complex projects this perhaps may only be at a summarised

level. Generally, for all main works and main subcontractors, it will assist in the management of

both the subcontractor and the project.

The diagrams are usually much easier to read than a detailed Gantt chart, making it a good tool

for reporting purposes and for illustrating the inter-relationship between different activities.

The LOB method is not simple though when dealing with a construction project that is broken

down into a large number of activities that are bound by numerous and complicated

relationships and other constraints. The ensuing diagram is not as effective and can prove more

complicated to read than the traditional Gantt chart.

Contractually, network analysis diagrams illustrating the project critical path(s) such as the Gantt

chart appear to be the requisite of clients, and are favoured in dispute resolutions.

Thus it appears that it is unlikely that the Line of Balance method shall, in the near future, take

over as being the main method used in the construction industry.

It has been seen though that there is much that the method can offer as a project management

tool, and may fruitfully be used in conjunction with a network analysis method such as the Gantt

chart.