The impact of design uncertainty in engineer-to-order project planning

doi:10.1016/j.ejor.2017.03.005

European Journal of Operational Research

Volume 261, Issue 3, 16 September 2017, Pages 1098-1109

https://doi.org/10.1016/j.ejor.2017.03.005 Get rights and content

Highlights

•
A stochastic dynamic program to connect design to project planning.
•
We show the monetary value of flexible hedging strategies.
•
Guidelines on where and when to develop flexibility and buffers in plans.

Abstract

A major driver of planning complexity in engineer-to-order (ETO) projects is design uncertainty far into the engineering and production processes. This leads to uncertainty in technical information and will typically lead to a revision of parts of the project network itself. Hence, this uncertainty is different from standard task completion uncertainty. We build a stochastic program to draw attention to, and analyse, the engineering-design planning problem, and in particular, to understand what role design flexibility plays in hedging against such uncertainty. The purpose is not to devise a general stochastic dynamic model to be used in practice, but to demonstrate by the use of small model instances how design flexibility actually adds value to a project and what, exactly, it is that produces this value. This will help us understand better where and when to develop flexibility and buffers, even when not actually solving stochastic models.

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.

References (28)

C. Artigues et al.
Maximization of solution flexibility for robust shop scheduling
European Journal of Operational Research
(2005)
F. Deblaere et al.
Proactive policies for the stochastic resource-constrained project scheduling problem
European Journal of Operational Research
(2011)
W. Herroelen et al.
Project scheduling under uncertainty: Survey and research potentials
European Journal of Operational Research
(2005)
W. Herroelen et al.
Critical chain project scheduling – Do not oversimplify
Project Management Journal
(2002)
A.J. King et al.
Modeling with Stochastic Programming
(2012)
H. Vaagen et al.
A multidisciplinary framework for robust planning and decision-making in dynamically changing engineering construction projects
C.M. Eckert et al.
The reality of design process planning
J. Emblemsvåg
Lean project planning in shipbuilding
Journal of Ship Production and Design
(2014)
W. Herroelen
Generating robust project baseline schedules
W. Herroelen et al.
A note on the paper “resource-constrained project scheduling: Notation, classification, models and methods” by brucker et al
European Journal of Operational Research
(2001)

T. Jørgensen et al.

Distributed project management

T. Jørgensen et al.

Improving project cost estimation by taking into account managerial flexibility

European Journal of Operational Research

(2000)

P. Kall et al.

Stochastic programming

(1994)

O. Lambrechts et al.

Time slack-based techniques for robust project scheduling subject to resource uncertainty

Annals of Operations Research

(2010)

Cited by (40)

Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm
2024, International Journal of Production Economics
This paper presents a new mathematical formulation for planning and scheduling activities of Engineer-To-Order (ETO) projects. It includes a new ETO strategy to reduce two principal impacts of the design uncertainty inherent in the ETO context: waste (of time and resources) and schedule instability. Our optimization approach is based on a two-level decision process to address, either sequentially or separately, the initial planning and the rescheduling stages. We also propose a hybrid Layered Genetic Algorithm combined with an adaptive Lamarckian learning process (LLGA). LLGA uses a new genetic representation (encoding format and decoding method) and a new cycle-avoidance procedure that guarantees solutions feasibility. LLGA is compared to the branch-and-cut procedure of CPLEX run on the proposed mathematical model on randomly generated instances with up to 340 operations. Our mathematical model shows a good performance for small and medium-sized instances, especially for the rescheduling stage. This performance deteriorates for larger instances (larger computing times and out-of-memory problems). However, the proposed heuristic is computationally stable and yields good-quality solutions in a reasonable computing time without requiring a large memory space. Our experiments also demonstrate the merits of our new ETO strategy in improving the robustness of the solutions.
Rearticulating supply chain design and operation principles to mitigate uncertainty in the Norwegian engineer-to-order shipbuilding sector
2023, International Journal of Production Economics
Engineering-to-order (ETO) systems are especially prone to high levels of uncertainty in demand, as well as from internal processes, supply side sources and their own control systems. Understanding and categorising the causes of uncertainty provides an opportunity for organisations to determine the principles and tactics for their mitigation. Previous scholars have developed a framework for ETO uncertainty reduction by the extension of the established ‘FORRIDGE’ principles from general manufacturing management. Although such a framework is claimed to be generic, it has only previously been applied in the UK construction industry. The aim of this paper is to determine—via a replication study—the reproducibility, reliability and validity of the ETO uncertainty reduction framework and extend it. A conceptual replication research study was undertaken involving a different population sample: the Norwegian shipbuilding sector. Based on previous research, we categorise ETO into two forms: innovate to order (ITO) and redesign to order (RTO). Targeting 10 Norwegian first-tier ship equipment manufacturers, the respondents were questioned regarding their sources of uncertainty and measures they adopted to mitigate these. Supply chain tactics for shipbuilding have been identified and mapped against the ETO uncertainty reduction principles and uncertainty sources for RTO and ITO types of ETO. Our study has highlighted the reliability of the FORRIDGE principles. We extend the original set of tactics established in the construction sector so that the ETO uncertainty reduction principles can be used in another sector, and we indicate the significance of different tactics for ITO and RTO types of ETO. We make a methodological contribution by showing the application of a conceptual replication research design in an operations management context. Further research is required to test the principles in other ETO-intensive sectors.
Engineer-To-order challenges and issues: A systematic literature review of the manufacturing industry
2023, Procedia Computer Science
Companies in engineer–to–order (ETO) manufacturing environments that seek efficiency gains through adopting a mass customisation strategy meet significant challenges. The implementation of the mass customisation (MC) strongly focuses on transitioning from mass production. The purpose of this study is to identify current areas of concern and operational challenges when adopting mass customisation principles in ETO companies. A Systematic Literature Review (SLR) was carried to evaluate the challenges the Portuguese Industry faces in the moulding companies’ sectors and how they are improving their ability to meet deadlines. The study will look at ways of boosting customer satisfaction by providing unique products at a relatively low cost. The study exposed issues of MC in ETO companies in general, it is critical to achieving more efficient use of resources, workflow, and innovative management methods and approaches to deal with the variability and complexity of this manufacturing system. The competitive pressure to achieve better efficiency and effectiveness in this type of organisation requires constantly searching for new concepts and tools that can be developed and applied. Furthermore, this paper explores the ETO companies' significant difficulties and the technical and scientific solutions used and proposed as its significant contribution, as well as a proposal for future research and development to increase ETO companies' resilience and performance level in managing their value chain and executing operations in response to customer requirements.
A model for advanced planning systems dedicated to the Engineer-To-Order context
2022, International Journal of Production Economics
This paper presents a new mathematical formulation for planning and scheduling activities in the Engineer To Order (ETO) context. Designed from an Advanced Planning System perspective, the proposed formulation not only schedules production operations but also takes into account the assembly, design, engineering, and validation phases. The definition of resources is thus generic and enables to model employees, finite capacity machines, and consumable materials. The definition of operations allows to represent short production operations, respecting precedence relations representing the assembly of elements, but also non-physical activities. Non-physical activities are longer, subject to validation, and applied once for multiple identical elements. Furthermore, to integrate planning and scheduling, the proposed formulation is not limited to time-based objectives but also considers financial and organizational aspects. The experiments carried out on instances with up to 100 operations show that our model performs well and requires reasonable computing times. Besides, we propose an ETO strategy that tends to validate the design of non-standard and highly uncertain items first and delay their production or purchase. Our integrated model governed by the proposed ETO strategy is compared to a model that mimics decision processes in existing industrial systems. The comparative study and experimental results highlight how this strategy yields robust integrated solutions that offer a good trade-off between the wastes caused by unpredictable changes in the BOM and the projects completion time.
A Two-Level Optimization Approach For Engineer-To-Order Project Scheduling
2022, IFAC-PapersOnLine
This paper presents a new formulation of the flexible job-shop scheduling problem with outsourcing options adapted for Engineer-To-Order (ETO) products. Our formulation enables modeling complex product structures with flexible precedence relations between elements and operations. Having a significant role in the ETO context, the specificity of non-physical operations (design and engineering) is taken into account. Indeed, non-physical operations are subject to a validation stage, can be iterated in case of non-validation, and are executed once for several identical elements. The proposed approach is governed by a new ETO strategy to overcome the impact of the design uncertainty and element cancellations (time and financial wastes). First, the production and purchase of the most uncertain elements are delayed at the latest while their design is validated early. Besides, in the presence of similar elements, an element can be saved when cancelled by being used as a sub-part of another one. The proposed approach sequentially solves two mathematical models. The first model aims to minimise the makespan and outsourcing costs. The second model maximizes the solution robustness and the ability of saving elements while being governed by the completion time and project cost, output of the first model. The obtained results and a comparative study show the efficiency and robustness of the proposal.
Exploring systemic factors creating uncertainty in complex engineer-to-order supply chains: Case studies from Norwegian shipbuilding first tier suppliers
2021, International Journal of Production Economics
Citation 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.
While it is recognised that there are varying uncertainty characteristics between industry sectors, there is little uncertainty research directly related to engineer-to-order (ETO) systems. A novel method is developed to identify the factors contributing to uncertainty in shipbuilding first-tier suppliers that inhibit the effective and efficient delivery of ETO products. The empirical data set comes from case-specific workshops involving cross-disciplinary staff from engineering, production, purchasing, planning and sales. The protocol included presentations by the researchers and the company, tours of the shopfloor and interactive sessions. The latter used ‘brown-paper’ exercises to map customer penetration-point locations, identify where uncertainties occurred and evaluate their impact-likelihood. The customer penetration-point mapping identified two ETO types; redesign-to-order (RTO) and innovate-to-order (ITO). The major challenges faced by ITO systems are caused through failures in (a) properly understanding customer requirements and translating those to product specification, (b) providing capacity and capability in engineering design teams at both first- and second-tier suppliers, (c) managing interfaces from customer through to second-tier suppliers. Engineering processes in RTO systems have poor customer configuration protocols leading to complex, overengineered products without pre-existing bill of materials. Engineering and production processes at both first- and second-tier RTO suppliers have extended lead-times with poor capacity availability. A change programme is suggested to reduce uncertainty requiring primary consideration of process and control aspects before addressing demand-side and then supply-side changes. The findings are evaluated by independent interviews indicating that the method and tools adopted have validity, and that the findings are commensurate with wider industry expectations.

View all citing articles on Scopus

View full text

Innovative Applications of O.R.The impact of design uncertainty in engineer-to-order project planning

Highlights

Abstract

Section snippets

Problem description

Existing literature

Stochastic programming formulation

Test case 1 – The value of flexible (two-step) designs

Test case 2 – Flexible (two-step) design is not available

Managerial implications – Guidelines on where and when to develop flexibility and time buffers

Conclusions

Acknowledgments

European Journal of Operational Research

European Journal of Operational Research

European Journal of Operational Research

Project Management Journal

The reality of design process planning

Lean project planning in shipbuilding

Journal of Ship Production and Design

Generating robust project baseline schedules

A note on the paper “resource-constrained project scheduling: Notation, classification, models and methods” by brucker et al

European Journal of Operational Research

Distributed project management

Improving project cost estimation by taking into account managerial flexibility

European Journal of Operational Research

Stochastic programming

Time slack-based techniques for robust project scheduling subject to resource uncertainty

Annals of Operations Research

Innovative Applications of O.R.
The impact of design uncertainty in engineer-to-order project planning