Mixed integer programming in production planning with backlogging and setup carryover : modeling and algorithms

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses associated with the one-time decisions made by other classical time-oriented decomposition algorithms. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable time

A Generic Decision Support Tool to Planning and Assignment Problems: Industrial Applications and Industry 4.0

Decision support tools are essential to help the management of industrial systems at different levels: strategic to size the system; tactical to plan activities or assign resources; operational to schedule activities. We present a generic and modular decision support tool to solve different problems of planning, assignment, scheduling, or lot-sizing. Our tool uses a hybridization between a metaheuristic and a list algorithm. The specification of the considered problem is taken into account in the list algorithm. Several tactical and operational problems have been solved with our tool: a problem of planning activities with resources assignment for hospital systems, a lot-sizing and scheduling problem taking into account the setup time for a textile application and for a plastic injection problem, and a scheduling problem with precedence constraints. At the strategic level, this tool can also be used as part of Industry 4.0 to design reconfigurable manufacturing systems. This paper summarizes some problems solved with the proposed tool and presents its evolution

On the Properties Evolution of Eco-Material Dedicated to Manufacturing Artificial Reef via 3D Printing: Long-Term Interactions of Cementitious Materials in the Marine Environment

This paper deals with the evolution monitoring of biomass colonization and mechanical properties of 3D printed eco-materials/mortars immersed in the sea. Measurements of tensile strength, compressive strength, and Young’s modulus were determined on samples deployed along the Atlantic coast of Europe, in France, United Kingdom, Spain, and Portugal. The samples were manufactured using 3D printing, where six mix designs with a low environmental impact binder were used. These mortars were based on geopolymer and cementitious binders (Cement CEM III), in which sand is replaced by three types of recycled sand, including glass, seashell, and limestone by 30%, 50%, and 100% respectively. The colonization of concrete samples by micro/macro-organisms and their durability were also evaluated after 1, 3, 6, 12, and 24 months of immersion. The results showed that both biomass colonization and mechanical properties were better with CEM III compared to geopolymer-based compositions. Therefore, the mixed design optimized according to mechanical properties show that the use of CEM III should be preferred over these geopolymer binders in 3D printed concrete for artificial reef applications

Artificial reefs built by 3D printing: Systematisation in the design, material selection and fabrication

The recovery of degraded marine coasts and the improvement of natural habitats are current issues of vital importance for the development of life, both marine and terrestrial. In this sense, the immersion of artificial reefs (ARs) in the marine environment is a way to stimulate the recovery of these damaged ecosystems. But it is necessary to have a multidisciplinary approach that analyses the materials, designs and construction process of artificial reefs in order to understand their true impact on the environment. For this reason, this paper presents the manufacture of artificial reefs by 3D printing, proposing designs with a combination of prismatic and random shapes, with different external overhangs as well as inner holes. For the definition of the artificial reef designs, criteria provided by marine biologists and the results obtained from a numerical simulation with ANSYS were taken into account, with which the stability of the artificial reefs on the seabed was analysed. Three dosages of cement mortars and three dosages of geopolymer mortars were studied as impression materials. The studies included determination of the rheological properties of the mortars, to define the printability, determination of the cost of the materials used, and determination of the mechanical strength and biological receptivity in prismatic specimens that were immersed in the sea for 3 months. To evaluate the environmental impact of the materials used in the production of the mortars, a Life Cycle Assessment (LCA) was carried out. In order to choose the mortars that encompassed the best properties studied, Multi-Criteria Decision Making (MCDM) was applied and the two best mortars were used for the manufacture of the artificial reefs. Finally, the advantages and disadvantages of the 3D printing process used were analysed. The results of the studies carried out in this research show that cement mortars have better characteristics for artificial reef applications using 3D printing, and that the technique applied for the manufacture of the artificial reefs allowed the digital models to be faithfully reproduced

Production planning and scheduling in the glass container industry: A VNS approach

Inspired by a case study, this paper reports a successful application of VNS to the production planning and scheduling problem that arises in the glass container industry. This is a multi-facility production system, where each facility has a set of furnaces where the glass paste is produced in order to meet the demand, being afterwards distributed to a set of parallel molding machines. Since the neighborhoods used are not nested, they are not ordered by increasing sizes, but by means of a new empirical measure to assess the distance between any two solutions. Neighborhood sizes decrease significantly throughout the search thus suggesting the use of a scheme in which efficiency is placed over effectiveness in a first step, and the opposite in a second step. We test this variant as well as other two with a real-world problem instance from our case study.

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012FAPESPFAPESP [2008/09953-2]CNPqCNPq [300713/2010-0]CAPES from BrazilCAPES from Brazil [CAPESBEX-1545/11-6, 246881]Erasmus Mundus External Cooperation Windows Programme from European CommissionErasmus Mundus External Cooperation Windows Programme from European Commissio

Assessment of Failures in Collaborative Human-Robot Assembly Workcells

Collaborative Human-Robot workcells introduce robot-assisted operations in small-volume production or assembly processes, where conventional automation is noncompetitive. Unfortunately, the collaborative work of humans and robots sharing the same work area and/or working on the same assembly operation may pose unprecedented problems and failure risks. Failure Mode, Effects and Criticality Analysis (FMECA) is a popular tool to design reliable processes, which investigates the potential failure modes from the perspective of severity, occurrence and detection. The traditional FMECA approach requires the assessment of failure modes to be carried out collectively by a group of experts. Nevertheless, in the field of Human-Robot collaboration, experts are often unlikely to agree in their judgements, due to the almost inexistent historical records. Additionally, the traditional approach is not appropriate for decentralized production/assembly processes. The paper revisits the traditional approach and integrates it with the ZMII-technique – i.e., a recent aggregation technique developed by the authors – which overcomes some limitations, including but not limited to: (i) arbitrary categorization and questionable aggregation of the expert judgments, (ii) disregarding the variability in these judgments, and (iii) disregarding the result uncertainty. The description is supported by a real-life application example