•36 methods showed a higher performance over the best approaches of the last survey.•The best methods are based on different hybridization frameworks.•The best methods embed more than one type of ...schedule improvement procedure.•Quite a few methods also embed diversity versus intensification mechanisms.•A high percentage of approaches rely on randomization and memories.
The Resource-Constrained Project Scheduling Problem (RCPSP) is a general problem in scheduling that has a wide variety of applications in manufacturing, production planning, project management, and various other areas. The RCPSP has been studied since the 1960s and is an NP-hard problem. As being an NP-hard problem, solution methods are primarily heuristics. Over the last two decades, the increasing interest in operations research for metaheuristics has resulted in a general tendency of moving from pure metaheuristic methods for solving the RCPSP to hybrid methods that rely on different metaheuristic strategies. The purpose of this paper is to survey these hybrid approaches. For the primary hybrid metaheuristics that have been proposed to solve the RCPSP over the last two decades, a description of the basic principles of the hybrid metaheuristics is given, followed by a comparison of the results of the different hybrids on the well-known PSPLIB data instances. The distinguishing features of the best hybrids are also discussed.
Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional ...enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.
Because of their cross-functional nature in the company, enhancing Production Planning and Control (PPC) functions can lead to a global improvement of manufacturing systems. With the advent of the ...Industry 4.0 (I4.0), copious availability of data, high-computing power and large storage capacity have made of Machine Learning (ML) approaches an appealing solution to tackle manufacturing challenges. As such, this paper presents a state-of-the-art of ML-aided PPC (ML-PPC) done through a systematic literature review analyzing 93 recent research application articles. This study has two main objectives: contribute to the definition of a methodology to implement ML-PPC and propose a mapping to classify the scientific literature to identify further research perspectives. To achieve the first objective, ML techniques, tools, activities, and data sources which are required to implement a ML-PPC are reviewed. The second objective is developed through the analysis of the use cases and the addressed characteristics of the I4.0. Results suggest that 75% of the possible research domains in ML-PPC are barely explored or not addressed at all. This lack of research originates from two possible causes: firstly, scientific literature rarely considers customer, environmental, and human-in-the-loop aspects when linking ML to PPC. Secondly, recent applications seldom couple PPC to logistics as well as to design of products and processes. Finally, two key pitfalls are identified in the implementation of ML-PPC models: the complexity of using Internet of Things technologies to collect data and the difficulty of updating the ML model to adapt it to the manufacturing system changes.
The Model-based Definition (MBD) approach is gaining popularity in various industries. MBD represents a trend in Computer-aided Design (CAD) that promises reduced time-to-market and improved product ...quality. Its main goal is to improve and accelerate the design, manufacturing and inspection processes by integrating drawing annotations directly onto a 3D model, therefore obviating the need to generate engineering drawings. However, its implementation throughout the whole product lifecycle has not yet been fully adopted. Traditional engineering drawings still play an essential part in the capture and distribution of non-geometric information. Based on thirty-four interviews conducted within the Engineering, Drafting, Configuration Management, Airworthiness and Certification, Manufacturing, Inspection and Knowledge Management departments from two Canadian Aerospace companies, the objective of this paper is to report on the main barriers that need to be overcome in order to fully implement the MBD initiative. In addition, the necessary elements and specific requirements needed to evaluate the capacities of emergent tools are proposed.
Purpose: Demand Driven Material Requirements Planning (DDMRP) aims to deal with variability by adjusting inventory levels while maintaining, or even increasing, customer service levels. This approach ...bridges the push and pull approaches. Even though it first made its appearance in 2011, research in this field remains relatively limited. This paper aims to measure the spatiotemporal evolution of the DDMRP, its scope and context of implementation, and the research lines studied in that field in order to identify areas that still need to be addressed by future researchers. Design/methodology/approach: The systematic literature review approach adopted in this paper examines research dealing with the DDMRP approach published in different languages between 2009 and 2020. To-date papers focused on the performance analysis and comparison, what differentiates this study is the focus on the scientific evolution level of DDMRP, the parameters, and contexts that should be more studied. Findings: The results show that DDMRP is not yet a mature method and that the robustness of the approach still needs to be tested. More research is also required to determine scientifically some setting parameters, how the proposed DDMRP could be implemented in different industrial contexts with existing information systems. Originality/value: Based on the evolution analysis of DDMRP, this study outlines its current state of maturity and its different shortcomings under a broader vision to make this method more complete on the scientific and industrial level.
Preparing and responding to disasters is a complicated task. One must balance coverage of SAR resources versus preparation cost. This article presents a method and solution to prepositioning UAV ...damage assessment and search teams in Oklahoma using historical tornado data. The approach is based on set covering and multi-station vehicle routing models. It also presents a method to robustify the solution in the event a UAV team cannot be activated to respond to the disaster. This can simulate a team unable to respond. Results show 70% more stations and teams being required when chance of a depot failure goes from 0 to 5% and 90% more stations required when 0-10%. We find that when trying to use a solution that does not account for depot failure, the system of UAVs cannot meet search completion targets in 3-4% of cases. These results demonstrate accounting for the chance of teams not being able to respond to domestic disasters is important and failing to do so means an increased chance of not being able to respond adequately to disasters and incorporating the chance of station failure has a profound impact on the number of stations needed.
Responding to tornado disasters resides at a unique intersection of search and rescue operations: it has attributes of wilderness and maritime search and rescue operations and search and rescue ...operations in the aftermath of earthquakes and hurricanes. This paper presents a method of attempting to leverage historical data to more efficiently identify the extent of the area damaged by a tornado. To assist in building and understanding the historical data, we also develop a method to generate tornado areas that react similarly to the limited historical data set. The paper successfully demonstrates the method of creating artificial tornado instances that can be used as a testing sandbox for the further development of tools when responding to tornado-type disasters. These artificial instances perform similarly in some important metrics to the historical database of tornado instances that we produced. This paper also shows that the use of historical tornado trends has an impact on the response method outlined in this article, typically reducing the standard deviation of the time it takes to fully identify the extent of the damage.
Set-based design (SBD), sometimes referred to as set-based concurrent engineering (SBCE), has emerged as an important component of lean product development (LPD) with all researchers describing it as ...a core enabler of LPD. Research has explored the principles underlying LPD and SBCE, but methodologies for the practical implementation need to be better understood. A review of SBD is performed in this article in order to discover and analyse the key aspects to consider when developing a model and methodology to transition to SBCE. The publications are classified according to a new framework, which allows us to map the topology of the relevant SBD literature from two perspectives: the research paradigms and the coverage of the generic creative design process (Formulation–Synthesis–Analysis–Evaluation–Documentation–Reformulation). It is found that SBD has a relatively low theoretical development, but there is a steady increase in the diversity of contributions. The literature abounds with methods, guidelines and tools to implement SBCE, but they rarely rely on a model that is in the continuum of a design process model, product model or knowledge-based model with the aim of federating the three Ps (People–Product–Process) towards SBCE and LPD in traditional industrial contexts.
The purpose of this article is to provide a brief review of methods and techniques developed for the most commonly studied decision-making problems in project planning and control over the last ...decade. These problems involve project representation, project scheduling, resource allocation, risk analysis, time and cost performance evaluation, time, cost, and cash flow forecasting, optimal timing of control points, and corrective action decision-making. We also review recent tools developed for project planning and control. The emphasis is on recent contributions, but several older yet important works are also cited. Our analysis shows an increasing attention to the stochastic nature of projects in planning and control decision and processes. Recent attention has also been put at improvements in existing project control techniques as well as developing new methods to automate data collection, process, and generate more integrated project plan. More importantly, our review highlights an important shift in the project planning and control research field, which has been largely dominated by the project scheduling literature in the past, as short term and reactive decision-making bring new challenges and opportunities to project organisations and researchers.
In the era of industry 5.0, digital twins (DTs) play an increasingly pivotal role in contemporary society. Despite the literature’s lack of a consistent definition, DTs have been applied to numerous ...areas as virtual replicas of physical objects, machines, or systems, particularly in manufacturing, production, and operations. One of the major advantages of digital twins is their ability to supervise the system’s evolution and run simulations, making them connected and capable of supporting decision-making. Additionally, they are highly compatible with artificial intelligence (AI) as they can be mapped to all data types and intelligence associated with the physical system. Given their potential benefits, it is surprising that the utilization of DTs for warehouse management has been relatively neglected over the years, despite its importance in ensuring supply chain and production uptime. Effective warehouse management is crucial for ensuring supply chain and production continuity in both manufacturing and retail operations. It also involves uncertain material handling operations, making it challenging to control the activity. This paper aims to evaluate the synergies between AI and digital twins as state-of-the-art technologies and examines warehouse digital twins’ (WDT) use cases to assess the maturity of AI applications within WDT, including techniques, objectives, and challenges. We also identify inconsistencies and research gaps, which pave the way for future development and innovation. Ultimately, this research work’s findings can contribute to improving warehouse management, supply chain optimization, and operational efficiency in various industries.
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