Application Of Network Analysis To Life Breweries Limited Onitsha For Time And Cost. – Complete project material


Network Analysis was applied to Life Breweries Ltd. Onitsha for time and cost.  Work breakdown structure, time-cost trade – off, critical path analysis and PERT model were invoked and time and cost variances were used to ascertain and monitor the progress of work on the brewery production project. The logical sequence of activities with their technological constraints, critical paths, project duration and floats were employed. The project duration through the critical path was 971.17hrs. It was then optimized through time-cost trade off to 831.17hrs. Also, the initial total cost of the project was N543001.68 and was optimized to N53641.68. The probability of completion of the project was also determined to be 95%.The Network Analysis proved to be an effective management technique in the planning, scheduling, monitoring and control of brewery project.














1.1     Literature Review.. 2

1.2     Statement of the Problem.. 5

1.3     Objective of the Study. 6

1.4     Significance of Study. 7

1.5     Scope of Work. 7

1.6     Organization of Work. 8

1.7     Definition of Terms. 8



2.1     Project Defined. 12

2.2     Project Management 13

2.3     Planning and Scheduling. 14

2.4     Time Resources. 19

2.4.1     Evolving the Work Plan. 19

2.4.2     Project Time Control 21

2.4.3     Work Breakdown Structure. 22

2.4.4     The Network Scheduling Method. 22

2.4.5     Developing the Network. 24

2.4.6     The Critical Path Concept. 24

2.4.8     Updating the Network. 26



3.1     Brief History. 27

3.2     Sources of Data. 27

3.3     Method of Data Collection. 28

3.4     Sample Size/Sampling Technique. 28

3.5     Method of Analysis. 29

3.5.1     Critical Path Method. 29

3.5.2     Resource Allocation. 30

3.5.3     Probability of Completion of the Project within a Scheduled Time. 30

3.5.4     PERT. 31

3.5.5     Time – Cost Trade Off 32


4.1     Data Presentation. 34

4.2     Data Analysis. 35

4.2.1     Work Breakdown Structure. 35

4.2.2     Sequencing the Project Work Packages. 38

4.2.3     Network Diagram.. 40

4.2.4     P.E.R.T Estimates. 40

4.2.5     Critical Path. 57


5.1 RESULTS 70




6.1       Conclusion. 71

6.2     Recommendations. 72




All forms of production process involve the transformation of resources into products. (Rovelle, 1976) observed that resources carried with it qualities of scarcity and value which implies that choice must be made in order to achieve the most optimal resource allocation and utilization in project execution.

On an individual basis or when charged  with the responsibility  for a task or program  involving additional engineering and supporting personnel, the engineering manager bears the basic responsibility for performing the best technical effort within specified schedule and cost constraints. In striving toward this goal, decisions throughout the work period can be greatly aided by a system providing accurate, up-to-date visibility of the cost and schedule picture. This is particularly significant in complex research, development and production programs involving a multiplicity of organizational levels engaged in numerous interrelated work items.Groover (1987) stated that production is a transformation process that converts raw material into finished products that have value in the market places. The transformation process usually involve sequence of steps, each step bring the material closer to the derived final state.

According to Michael and Tom (1995), the wish to produce a product yielding profit to the brewer has surely always been a prime driving force. Success went to those who could control their processes, minimize losses, maximum yield and produce consistent quality. This brings to mind the importance of these two main concepts of time and cost.



Jellouli et al (2007) presented a paper on optimal (s, S) policies for production planning in stochastic manufacturing systems with failures. Their models, considered a one- machine system which produces one type of product. Two cases were considered. The first one considered failure in the production process and the second one considers failure in the distribution process. Parameters characterizing the system are stochastic and they are assumed to be exponentially distributed.

In his effort to tackle the problem of improper planning and scheduling in production process, Jaikumar (1974) formulated a long range model which is essentially a resource constrained model that has a linear programming formulation with a profit maximization objectivefunction. The long range plan fixes the discretionary marketing variables such as the selection of product line and the timing and extent of promotional sales.It estimates manpower requirement and establishes the raw material procurement plans. The number of production ho.urs in given week is determined by the long range plan and the product to produced in each of the lines is allocated by the algorithm. Sequentially, decisions are made in the following order:

  1. What product to produce
  2. When to produce
  3. Which line to produce it in
  4. The shift multiple to produce it.

Moore et al (1980) modeled and simulated the review process of an academic journal using the network technique, GERT.The manuscript review process of most quality academic journals consists of various stages involving system looping, multiple outcomes and probabilistic branching. In other words, an article review process can be considered as a complex stochastic network. GERT (Graphical Evaluation and Review Technique) according to Moore et al is an appropriate modeling technique for the portrayal and analysis of a journal review process because of its flexibility and applicability to scholastic network systems.

Hochwald et al (1966) describes a system for internal organization, schedule and cost control of complexresearch and development programs with automatic features for generating customer-required external reports and summaries. The system includes automatic data evaluation features such as earned value and percent physical completion computations, performance indexes, projections to completion etc.

Basically, SCOPE (Schedule, COst and PErformance) is a data processing system whichenables collection of cost and schedule data at the “grass roots” or lowest cost control level with a relatively simple input and updating format.Advanced data processing technology is used to process and extract data with the flexibility required to provide information required for cost and scheduled control at each organizational level, as well as reporting data at the program level.

Schniederjans et al (1978) demonstrated the use of a simulated transportation method as an approach to developing an instructional guide that is operational, flexible and feasible for planning truck rental needs in a way to minimize cost. The unformational impact of this approach aids not only the internal operations but also external relations with truck renting companies by providing a more accurate measure of the anticipated demand on rental equipments, thus allowing the rental companies an opportunity to meet this demand.

Brucker et al (1999) stated that project scheduling is concerned with single- item or small batch production where scarce resources have to be allocated to dependent activities over time. They reviewed exact and heuristic algorithms for the single-mode and the multi-mode case, for the time-cost tradeoff problem, for problems with minimum and maximum time lags, for problems with other objectives than make span minimization and problems with stochastic activity durations. They provided a classification scheme i.e. a description of the resource environment, the activity characteristics, and the objective function, respectively which is compatible with machine scheduling.

Badiru (1991) presented simulation as a useful analytical tool for project network analysis. A computer program namedSTARC is used to illustrate the effectiveness of computer simulation for project planning.

Several works has been carriedout using different models and network techniques aimed at reducing time andcost. However, in developing algorithms to solve specific problems, the structure of the algorithm and the solution procedures are often influenced by the environment in which the problem is posed. Moreover, no previous work has been done on the application of network analysis to brewery production process.



Lack of proper planning and control has been identified as a major cause of project failure in this country. Poor planning and monitoring or lack of these has led to poor execution of jobs, time and cost overruns, non-acceptance of jobs by clients, un-attainment of project goals etc. For a project to be fully accomplished it must meet time and monetary criteria, effectiveness criterion and client satisfaction. It is also an established fact that breweries are folding up in this country largely due to the problem stated above. It is therefore the intention of this work to see how network analysis can be applied for effective planning, monitoring and control of operations of Life Breweries Limited to meet time and cost requirements.



The objectives of this work are:

  • To make an in-depth study of network analysis
  • To demonstrate the application of network analysis to Life Breweries Limited, Onitsha
  • To show that network analysis is a useful technique in the planning, monitoring and control of an engineering project.
  • To determine the possible effects of a delay in project activity on cost and time schedule of an engineering project.
  • To make the necessary recommendations for policy decisions.


The significance of this study is that it will provide a data base for planners, policy maker, project and production managers towards planning and executing a successful brewery production project. They will appreciate the fact that brewery operations can be better managedusing network analysis. Operating successfully within budget and on schedule enhances progress and this gives joy to all project participant including customers. No previous work has been done on the application of network analysis to brewery production process.



This work is on the application of network analysis to life breweries Ltd Onitsha for time and cost. Project and project management will be defined and the study covers such areas of project management as planning and scheduling. Discussion of network process and this includes logical sequencing of activities, work breakdown structure, Programme Evaluation and Review Technique (PERT), Critical Path Method (CPM). Cost and time schedules of brewing process are worked out. Deviations from plan, cost and schedule variance were worked out and analyzed.



This work is grouped into six chapters – chapter one on introduction, to chapter six, on conclusions and recommendations. Chapter three is on methodology while chapter four deals with data presentation and analysis.



Activity –                     An operation or process consuming time and possibly other resources.

Activities duration –     This is the estimated or actual time required to complete an activity

Backward pass   –        The procedure by which the latest event times for a

Network are determined

Cost                    –         Cost incurred by the client or sponsor of a project from

the inception through to completion.

Cost overrun      –         The excess of actual cost expenditure over planned


Critical path       –          This is that sequence of activities which determines the

total time for the task. It is the path from a start event to an end event, the total duration of which is not less than that of any other path between the same two events.

Dummy (Activity)-        This is a logical link, a constraint which represents one

specific operation. It is an activity which does not consume time or resources used to construct a network, usually represented by a broken arrow.

Earliest finish time –      This is the earliest possible time atwhich an activity

can finish without affecting the total project time or the logic of the network.

Event                  –          A state in the progress of a project after the completion

of all preceding activities but before the start of any succeeding activity.

Float                   –          A time available for an activity or path in addition to

its duration. It is essentially a properly of activities and is the difference between the time necessary and the time available for an activity.

Forward pass     –        The procedure whereby the earliest event times for a

network are determined.

Free float            –          This is the amount of spare time available to any

activity provided that any delay in it does not cause any subsequent activity to be delayed. It is part of the total float.

Head Event        –          The event at the finish of an activity

Latest start time –        This is the latest possible time by which an activity can

start without affecting either the total project time of the logic of the network.

Network             –          A network is a diagrammatic representation for a

project incorporating in a logical sequence, the various

activities which together make up the project.

PERT                 –          A name for a network analysis technique formed from

the word – programme evaluation and review technique.

Project                –          A project is a collection of tasks that are related to

each other overtime, with a beginning and an end, whose purpose is to achieve specific goal.

Project manager –        The person responsible for the overall management of

the project.

Tail Event          –          The event at the beginning of an activity.

Time                   –          Time taken to complete the project from inception to


Time overrun     –          excess of actual time taken over planned time or


Total float          –          This is the maximum amount of spare time available to

any activity without minding if any delay in the activity affects the timing of other activities provided that the overall project time is not extended.


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