Critical Chains in Project Management

Over years, managers and other leaders have developed and implemented several methods to effectively manage projects. These methods have recorded varying success in use and applicability. Project management and schedule traditional methods contain numerous problems which are considered dire to the project’s overthrow and plan stability (Hong & Ji-Hai, 330). Traditional methods of project management, Program Evaluation and Review Technique (PERT); Design Structure Matrix (DSM) and Critical Path Method (CPM) are successful in application of running of individual projects, but cannot be successfully applied in multiple projects’ parallel management. The attempts to resolve this disadvantage led to the development of critical chain project management method (CCPM).

Critical chain is described as the project network’s longest series of activities, after resource contentions’ resolution (Rezaie, Manouchehrabadi & Shirkouhi, 481). Basing on his theory of constraint (TOC), Goldratt, introduced the method of critical chain project management (CCPM) (Rezaie, Manouchehrabadi & Shirkouhi, 481; Li, Gong &Kou, 485; Hong & Jihai, 330). The key advantages of CCPM are its simple understanding and visual imagery while its chief weakness is failure of reflecting the constraints, process logic and critical work (Hong & Jihai, 330). Therefore, it has limited application. The development of critical chain theory was subsequent to the development of the following methods: Critical path method by United States Rand Corporation and Dupont, Program Evaluation and Review Technique (PERT) by Allen and Hamilton firm (Yu-Cheng, cited in Hong & Ji-Hai, 330), the Graphical Evaluation and Review Technique (GERT) by Apollo Lunar Landing Program (Jin-Bo, Zhen-Ming & zhi, cited in Hong & Ji-Hai, 330) and Venture Evaluation Review Technology (VERT) (Lewis, cited in Hong & Ji-Hai, 330).

Critical chain theory was introduced in the year 1997 basing on TOC. It advanced the CPM and PERT methods of project management from the limited resources’ viewpoint. The critical chain theory incorporates cognitive, resource-constrained and physiological factors, together with the bottlenecks of projects; those critical factors resulting in the project’s time of delay. This theory utilizes conduct science, which covers up the limitation of traditional project management, in management of project schedule. This theory follows seven steps (Hong & Ji-Hai, 331):

  1. The structure of work breakdown establishment
  2. Activities definition
  3. Network chart drawing
  4. Critical chain (constraints) identification
  5. Restraint use; project activities’ times’ estimation, feeding buffer and project buffer and   resource buffer identification
  6. Small non-critical path chain identification; and
  7. Project’s critical chain schedule scheming

Time estimation and buffers are the key components of critical chain. Time estimation refers to the length of the anticipated activities’ time of completion whereas buffers denote the time added to the anticipated completion time of the activities to offer safe completion of the whole project without delays (Rezaie, Manouchehrabadi & Shirkouhi, 482). Despite activities containing more safety times, projects fail to be completed on due dates. This is attributed to two reasons according to Goldratt; Parkinson law that argues the idea of work expanding itself to use extra time and student syndrome proposing people’s postponement of project’s work by to focus on their individual undertakings, up to the time they feel they will complete the project’s work on time. There exist two buffer types in critical chain; feeding buffer (protecting the chain from non-critical chains’ uncertainty) and project buffer (absorbing the critical chain activities’ variability and protecting the chain from uncertainty) (Rezaie, Manouchehrabadi & Shirkouhi, 482).

Rezaie, Manouchehrabadi & Shirkouhi (483) suggests a different method of estimating the activities’ time. This presented method bases on the fact that relation of time safety and each activity’s duration; estimating each activity’s embedded safety time. The extensively used method of uncertainty measurement considered duration as the difference between pessimistic time and average estimate. On contrary, the method presented by Rezaie, Manouchehrabadi and Shirkouhi determines the coefficient of statistical distributions’ dispersion. The coefficient is given by dividing standard deviation by the distribution mean.

Li, Gong and Kou (486) describes an algorithm of critical chain under subheadings ant colony optimization, critical chain algorithm and algorithm steps. In their work, they view the scheduling of resource-constrained projects as a problem of generalized optimization. Ant colony optimization, devises virtual ants that explore varying routes, and eventually leave the virtual pheromone steady disappearance. It explains that, the best route is chosen on the principle of “mutually pheromone closer to the line” (Li, gong and Kou, 486). This method involves the main idea, heuristic information and information update.

They argue that the method of critical chain employs critical chain and not critical path, in its algorithm. The critical chain’s activity set and critical chains number rely on the RCPSP solving process. They suggest that methods of critical chain ought to solve buffer setting in critical chain and activity duration’s cut coefficient. The duration cut ratio is given by dividing the project’s time excluding resource constraint (T1) by the project’s ACO length (T2). The buffer is greater than or equal to zero, but less than or equal to the difference between duration excluding resource constraint consideration (t2) and duration including limited resource consideration (t1), that is t2-t1.

The algorithm steps part describes the procedures of implementation. It involves three steps. First: determining project’s length and critical path excluding resource constraint’s consideration and ACO’s use in obtaining the project length, and critical chain. Second: cut ratio computation and modification in presence of other feasible alternatives of resource utilization. Third: modification of the improved critical chain using the activity flexible and project’s flexible coefficients Li, Gong & Kou, 487).

  • Works cited
  • Hong, L. J. R. & Ji-Hai, L. J. Critical Chain Management Based Heuristic Algorithm for   Multiple Resources-Constrained Project. Seminar on Business and Information Management, 2008,    330-335.
  • Li, K., Gong, L. & Kou, J. resource-constrained project scheduling based on ACO-Critical Chain Method. International Workshop on Computer Science and Engineering, 2009, (2), 485-489.
  • Rezaie, K., Manouchehrabadi, B. & Shirkouhi, S. N. duration estimation: a new approach in         critical chain scheduling. Asia International Conference on Modeling and Simulation,     2009, (3), 481-484.

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