Innovative Applications of O.R.The impact of design uncertainty in engineer-to-order project planning
Section snippets
Problem description
We consider a project production system following the engineer-to-order (ETO) approach where design, engineering and production do not commence until after a customer order is confirmed (Rudberg & Wikner, 2004). This approach is used to create products that are tailored for each customer and is used in, for example, shipbuilding and off-shore oil and gas installations. A typical feature of ETO projects, especially in the case of complex orders such as offshore ships, is a continuous dialogue
Existing literature
The engineering design process connects the phases of basic (preliminary) design with detailed design and project planning and scheduling, where one design alternative normally excludes other alternatives. Most commonly, design planning and project scheduling are treated as separated stages. This separation is problematic in an uncertain world where speed to market drives competitiveness, and design activities are necessarily performed concurrently with planning and execution (Eckert, Clarkson,
Stochastic programming formulation
In this section, we build a model for the case of stochastic changes in design specifications, while keeping the task durations deterministic. The main reason for this separation is that our goal is to study the impact of design uncertainty on planning, and adding uncertainty in task durations would just make the results more difficult to interpret. As discussed in Section 1, our problem understanding (supported by contextual exploratory studies) suggests that the most critical variation is
Test case 1 – The value of flexible (two-step) designs
For the first test case, we use the project presented in Section 3.1. The dependency graph is presented in Fig. 2, where we omit all the undo activities for the sake of readability. The activities’ durations are presented in Table 1. Note that the flexible two-step paths to PA, PB, DA, and DB take one period longer than the non-flexible direct activities.
The planning horizon consists of 11 half-week periods, so the maximal duration is 5.5 weeks. We assume that the customer has asked for design
Test case 2 – Flexible (two-step) design is not available
Our second test case is motivated by a situation where we are planning outfitting a vessel with four possible equipment designs A, B, C, and D, but we lack the option of a flexible (two-step) design solution. This can be seen as an example of uncertainty where the outfitting equipment differs substantially with respect to the scope of the vessel. This is a situation faced by shipowners when ordering a vessel before the exact nature of the sea operations is fixed. Assume we know that the
Managerial implications – Guidelines on where and when to develop flexibility and time buffers
The results indicate that the optimal objective function value in a static scheduling model cannot be trusted as a reliable estimate for project costs. An update to new customer requirements is obviously necessary, and using deterministic static models for budgeting and scheduling purposes will lead to potentially high cost overruns (up to 100% in our cases). A proactive strategy that captures the value of future design decisions improves the expected project costs, and we show such cost
Conclusions
With this paper we extended the scope of research on project scheduling, by connecting design to project planning in a stochastic dynamic model, representing a proactive strategy. Our main motivation was to understand the impact of design uncertainty on project planning, as without this knowledge it is difficult to achieve good solutions for concurrency in design, engineering and execution. To deal with the problem, we developed a stochastic programming model. For practical reasons, we focused
Acknowledgments
The authors thank anonymous reviewers for valuable comments. This paper is part of the competence-building research project NextShip, under Norwegian Research Council grant agreement 216418/O70.
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2021, International Journal of Production EconomicsCitation Excerpt :Mello et al. (2015) emphasized the complex interaction between actors in the interface between production and engineering, and suggested that overlapping project activities can make coordination of engineering and production very difficult, especially for large complex ships where customer changes are common. Vaagen et al. (2017) developed a stochastic model to understand the role of design uncertainty for project planning at the yard. They focused on strategic components where size, technical specifications, or even choice of supplier, might be changed late in the process by the customer, and demonstrated that to perform design and execution activities concurrently might be costly.