طراحی چندمنظوره بافر در حال ساخت برای زمان بندی مکرر پروژه های ساختمانی

Variability in production is one of the largest factors that negatively impacts construction project performance. A common construction practice to protect production systems from variability is the use of buffers (Bf). Construction practitioners and researchers have proposed buffering approaches for different production situations, but these approaches have faced practical limitations in their application. A multiobjective analytic model (MAM) is proposed to develop a graphical solution for the design of Work-In-Process (WIP) Bf in order to overcome these practical limitations to Bf application, being demonstrated through the scheduling of repetitive building projects. Multiobjective analytic modeling is based on Simulation–Optimization (SO) modeling and Pareto Fronts concepts. Simulation–Optimization framework uses Evolutionary Strategies (ES) as the optimization search approach, which allows for the design of optimum WIP Bf sizes by optimizing different project objectives (e.g., project cost, time and productivity). The framework is tested and validated on two repetitive building projects. The SO framework is then generalized through Pareto Front concepts, allowing for the development of the MAM as nomographs for practical use. The application advantages of the MAM are shown through a project scheduling example. Results demonstrate project performance improvements and a more efficient and practical design of WIP Bf. Additionally, production strategies based on WIP Bf and lean production principles in construction are discussed.

Variability in production is one of the largest factors that negatively impacts construction project performance. It can induce dynamic and unexpected conditions, unsteadying project objectives and obscuring the means to achieve them. To understand the effect of variability on production processes, Hopp and Spearman [1] distinguished two kinds of variability in manufacturing systems: 1) the time process of a task and 2) the arrival of jobs or workflow at a workstation. Koskela [2] proposes a similar classification to variability in construction systems, where the processes duration and the flow of preconditions for executing construction processes (e.g., space, equipment, workers, component and materials, among others) are understood as variable production phenomena. From a practical standpoint, construction practitioners everyday observe this behavior in the project environment through varying production rates, labor productivity, schedule control, cost control, etc. Several researchers have shown that variability is a well-known problem in construction projects, which leads to a general deterioration of project performance on dimensions such as: cycle time [3], [4], [5], [6] and [7], labor productivity [8] and [9], project cost [10], planning efficiency [11] and [12], among others. A way to deal with variability impacts in production systems is through the use of buffers (Bf). By using a Bf, a production process can be isolated from the environment as well as the processes depending on it [2]. Buffers can circumvent the loss of throughput, wasted capacity, inflated cycle times, larger inventory levels, long lead times, and poor customer service by shielding a production system against variability [1]. Hopp and Spearman [1] define three generic types of Bf for manufacturing, which can be applied in construction as: 1. Inventory: In-excess stock of raw materials, Work in Process (WIP) and finished goods, categorized according their position and purposes in the supply chain [13]. 2. Capacity: Allocation of labor, plants and equipment capacity in excess so that they can absorb actual production demand problems [14]. 3. Time: Reserves in schedules as contingencies used to compensate for adverse effects of variability. Float in a schedule is analogous to a Bf for time since it protects critical path from time variation in non-critical activities. Theoretically, the analysis of Bf in this paper is based on lean production principles. Lean production is a management philosophy focused on adding value from raw materials to finished product. It allows avoiding, eliminating and/or decreasing waste from this so-called value stream. Among this waste, production variability decreasing is a central point within the lean philosophy from a system standpoint [15]. Lean production, as applied in construction, focuses mainly on: i) decreasing non-value-adding activities or waste (e.g. wait times); ii) increasing value-adding activities efficiency (e.g. process duration); iii) decreasing variability [2]; and iv) optimizing the production system performance as a whole [15]. In construction, current buffering practices generally follow an intuitive and/or informal pattern, leading to poor variability control [3], [5], [7], [14], [16], [17], [18], [19], [20], [21], [22], [23] and [24]. Recently, several researchers and practitioners have proposed new Bf approaches to manage variability in construction, which have allowed industry to partially avoid informal and intuitive methods of designing and managing Bf in construction [3], [7], [14], [18], [25], [26] and [27]. However, these methods have been either too theoretical in design or too difficult to apply in practice. In Fact, there is limited evidence showing any use of practical buffering design approaches in construction practice [28]. This paper presents a buffering approach that is applicable for Work-In-Process (WIP) in repetitive building projects. In construction, WIP can be defined as the difference between cumulative progress of two consecutive and dependent processes, which characterizes work units ahead of a crew that will perform work (e.g., work units that have not been processed yet, but that will be). This definition of WIP is clearer in repetitive projects where processes are repeated continuously (e.g. highways, railways, pipelines, sewers, etc.) or in discrete repeated units (e.g. high-rise buildings, multistorey building, and repetitive residential projects, etc.) [29]. Existing research explores, the use of WIP Bf in repetitive projects, both implicit and explicitly, and demonstrates the limitations of its application [3], [5], [23], [26], [27], [28], [30], [31], [32], [33] and [34]. This body of research suggests opportunities to improve the use of WIP Bf and to overcome practical limitations in current buffering approaches. However, WIP Bf application in a production system is neither an apparent nor a direct task. The use of WIP Bf is controversial from a lean production perspective since the lean ideal suggests that zero inventories, or non-buffered production systems, are desirable [15]. Nevertheless, a production system without WIP implies a production system without throughput. Hopp and Spearman [1] recognize this issue and state that pull mechanisms in a production system do not avoid the use of buffers. However, the use of large WIP Bf to ensure throughput in production systems will inherently increase cycle times and costs. Therefore, it appears that a ‘balance problem’ exists between the use of WIP Bf to reduce variability impacts and overall production system performance based on lean principles. Simulation–Optimization (SO) modeling can address this balance problem. Simulation–Optimization modeling can help to design appropriate WIP Bf sizes by addressing the trade-off between decreasing variability through larger WIP Bf sizes and increasing production system performance by lowering WIP Bf sizes to the theoretical limit of zero. In designing optimal WIP Bf sizes, SO modeling must account for different project objectives (project cost, time and/or productivity). Computer simulation is being actively applied as a research tool to investigate how buffering strategies affect construction production systems [3], [14], [23], [30], [31], [35] and [36]. To date, research has only addressed specific cases of buffering strategies and it has not effectively addressed the balance problem. The first application of SO to model Bf in construction was proposed by [5], and a similar SO approach to model Bf in a construction scheduling context was also developed by [33]. Though both explicitly addressed the balance problem in theory, the research was not applied to an actual WIP Bf design in construction.

This research has demonstrated the feasibility of designing WIP Bf strategies for construction projects to decrease the negative impacts of variability in production processes and to increase project performance. By doing so, a MAM to design WIP Bf based on SO modeling and Pareto Front concepts was proposed. A SO approach was tested and validated by means of two case studies, allowing for different levels of performance improvement after the application of WIP Bf strategies. However, the magnitude of the improvements depends on the context of the application (e.g., seasonality, execution complexity, types of processes, variability levels, modeling assumptions, etc.), the project decision makers and site personnel willingness to apply buffering strategies, and the level of supply chain control. The MAM was developed as nomographs using only two production variables: time and production rates. This framework allowed for a simple and practical method of designing WIP Bf for scheduling repetitive building projects with independence of cost. The framework is supported by evidence from the SO case studies. This statement was demonstrated through cost improvements obtained in the project examples after application of the MAM. It was apparent that the use of MAM reduced the interdependencies between processes for a given level of variability. This paper provides the first application of the MAM approach to generalize the application of WIP Bf in construction through simple and practical means. It is hoped that this approach will facilitate the use of WIP Bf in the construction industry and contribute to reduce the gap between theory and practice in the body of knowledge for the buffer management. Because there is variability in construction, more rational use of buffers is necessary. In addition, further research is necessary in order to produce more nomographs to design WIP Bf for other production situations and contexts, stimulating its generalization and facilitating its industry adoption as a practical tool. This paper also documents a two-level methodology, both strategic and tactical, to design WIP Bf. It is demonstrated in the scheduling process for repetitive building projects. The MAM approach can be applied at the strategic level, while the SO approach can be applied at the tactical level. This methodology can reduce the management cost and supervision effort of labor, due to the fact that labor permanency on site is decreased while its efficiency is increased. Alternatively, the increment of labor efficiency can be related to more profits for subcontractors given the reduction of labor permanency in projects. As a result, labor can be assigned to other projects. This methodology can also reduce on-site waste, decreasing waiting times and stimulating continuous resource utilization. The methodology can also contribute to reduction of rework by assuring the quality of WIP for downstream crews (stimulation of value-adding activities). This paper is part of an ongoing research to generalize the design and management of WIP Bf in repetitive projects based on lean production principles. The next step in this research is to develop WIP Bf management process at the operational level (not only scheduling, but also planning and controlling). Currently, this is being approached through the development and investigation of decision-making models to forecast and control more rationally on-site production commitments in construction, including the management of WIP Bf designed at lower production levels. Future articles will address this topic.