An MILP-based approach to the short-term scheduling of make-and-pack continuous production plants

Many fast moving consumers good manufacturing companies produce a moderate number of intermediates that are combined in many different ways to generate an enormous variety of end products. To do that, such companies usually run continuous production plants in a make-to-stock environment. The process structure includes a fabrication area yielding basic intermediates that are stocked in a large middle storage space, and a packing sector where finished products usually comprising several intermediates are manufactured. Intermediates all undergo the same sequence of processing stages and the production of any campaign is sequentially allocated to an ordered set of end products. An MILP continuous time scheduling problem formulation handling independently assignment and sequencing decisions and considering sequence-dependent setup times and specific due dates for export orders has been developed. The problem objective is to meet all end-product demands at minimum make-span. The proposed model is able to account for assorted products, multiple campaigns for a particular intermediate even at the same unit and the consecutive allocation of an intermediate campaign to different finished products. Moreover, it can easily embed powerful preordering rules to yielding reduced MILP formulations so as to tackle real-world industrial problems at low computational cost. The approach has been successfully applied to large-scale industrial examples. RID="*" ID="*" The authors acknowledge financial support from FONCYT under Grant 14-07004, and from “Universidad Nacional del Litoral” under CAI+D 121. Correspondence to: J. Cerdá     

SMT production scheduling: a generalized transportation approach

A generalized transportation model is first formulated for the scheduling of Surface Mount Technology (SMT) production. Its dual form is next discussed. By specially coding the SMT scheduling problem, it is unnecessary to develop the constraint matrix for the dual. The simplex method is not applicable for this problem due to its sparse data structure. An efficient algorithm for the dual model is then developed from the idea of the revised simplex method. To illustrate the algorithm, a numeric example is presented.     

Master production scheduling: a multiple-objective linear programming approach

This paper describes and discusses a mathematical model for developing a Master Production Schedule. The model considers multiple objectives and several typical constraints. The input parameters to the model are determined and an example is solved to illustrate the procedure.     

An integer programming approach to elective surgery scheduling

The scope of this work covers a real case of elective surgery planning in a Lisbon hospital. The aim is to employ more efficiently the resources installed in the surgical suite of the hospital in question besides improving the functioning of its surgical service. Such a planning sets out to schedule elective surgeries from the waiting list on a weekly time horizon with the objective of maximizing the use of the surgical suite. For this purpose, the authors develop an integer linear programming model. The model is tested using real data obtained from the hospital’s record. The non-optimal solutions are further improved by developing a custom-made, simple and efficient improvement heuristic. Application of this heuristic effectively improves almost all non-optimal solutions. The results are analyzed and compared with the actual performance of the surgical suite. This analysis reveals that the solutions obtained using this approach comply with the conditions imposed by the hospital and improve the use of the surgical suite. It also shows that in this case study the plans obtained from the proposed approach may be implemented in real life.     

An approach to optimization with heuristic methods of scheduling

This paper describes an approach to the optimization of heuristic scheduling in batch and jobbing manufacture. The approach is based upon the use of a composite weighted priority index to resolve conflicts between operations in order to meet a predefined management objective function. The effects of combined despatching parameters in the priority index are investigated and examples are given of the resulting response surfaces. Using the techniques of harmonic analysis a model of the underlying surface trend is identified and used to predict the location of optimal schedules. Typical experimental results are presented which suggest that the proposed method compares favourably with traditional scheduling techniques.     

A tabu search heuristic for scheduling the production processes at an oil refinery

In this paper we present a tabu search heuristic which can be used for scheduling the production at an oil refinery. The scheduling problem is to decide which production modes to use at the different processing units at each point in time. The problem is a type of lot-sizing problem where costs of changeovers, inventories and production are considered. In the suggested tabu search heuristic we explore the use of variable neighbourhood, dynamic penalty and different tabu lists. Computational results are presented for different versions of the heuristic and the results are compared to the best-known lower bound for a set of scheduling scenarios.     

A project scheduling approach to production planning with feeding precedence relations

In Manufacturing-to-Order or Engineering-to-Order systems producing complex and highly customised items, each item has its own characteristics that are often tailored for a specific customer. Project scheduling approaches are suitable for production planning in such environments. However, when we consider the production of complex items, the distinct production operations are often aggregated into activities representing whole production phases. In such cases, the planning and scheduling problem works on the aggregate activities, considering that, in most cases, such activities also have to be manually executed. Moreover, simple finish-to-start precedence relations no longer correctly represent the real production process, but overlapping among activities should be allowed. In this paper, a project scheduling approach is proposed for production planning in Manufacturing-to-Order systems. The Variable Intensity formulation is used to allow the effort committed to the execution of activities to vary over time. Feeding precedences are developed to model generalised precedence relations when the execution mode of activities is not known a priori. Two mathematical formulations of these precedence relations are proposed. The formulations are applied both to randomly generated instances and to an industrial system producing machining centres and are compared in terms of computational efficiency.     

An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.     

A fuzzy logic approach to an integrated maintenance/production scheduling algorithm

Scheduling algorithms play an important role in manufacturing systems as a means of meeting customer demands. On the other hand, fuzzy logic, which has been successfully implemented in many engineering applications, including the recent work of Vanegas and Labib (2001a,b), has an ability to produce a more gradual transition. This paper presents an algorithm for transforming maintenance data to shop floor information. These shop floor data are then used via a fuzzy-logic based scheduling algorithm to determine optimal production systems control policies. The frequency of breakdowns and the mean number of parts required are used as inputs to the fuzzy logic controller. These inputs are transformed to the mean part arrival rate. The output is then fed to the scheduling algorithm. Finally, the optimal batch size is calculated. The algorithm is demonstrated with simulation.     

An approach to computer integrated production management

A new paradigm is proposed for the realization of computer integrated production management. Computer integrated manufacturing (CIM) can never be constructed just by combining the automated devices available at present, such as CAD, CAM, CAPP and MRP systems. To realize successful CIM, the automation of friendly communication between experts is required, which plays a most important role in the integration of the various functions of production management. This points to the importance of computer integrated production management. In order to confirm the validity of the paradigm proposed in this paper, a prototype in process planning has been developed which aims at integration with CAD.     

Optimization of a refinery scheduling process with column generation and a quantum annealer

Optimization and Engineering - This study focuses on the optimization of a refinery scheduling process with the help of an adiabatic quantum computer, and more concretely one of the quantum...     

An approach to the implementation and verification of abstract data

Abstract

The concept of abstraction can be used to simplify and formalize the design of software. However, most of the existing techniques based on abstraction only consider the control structure but not the data structures in the software. The transformation of a data abstraction, i.e., an abstract data type, to a physical data structure is a complicated process. It is composed of three major parts: a specification technique for describing a data abstraction; a deriving process for deriving the representation of the abstraction based on the specification; and a verification method for verifying the correctness of the specification and the representation of the abstraction. In this paper, we will concentrate on the last two problems, and it is assumed that the algebraic specification technique is used for describing abstract data types. Also, we will use examples to illustrate the use of the proposed approach.     

Design of predictable production scheduling model using control theoretic approach

As one of the most important planning and operational issues in manufacturing systems, production scheduling generally deals with allocating a set of resources over time to perform a set of tasks. Recently, control theoretic approaches based on nonlinear dynamics of continuous variables have been proposed to solve production scheduling problems as an alternative to traditional production scheduling methods that deal with decision-making components in discrete nature. The major goal of this paper is to improve predictability and performance of an existing scheduling model that employs the control theoretic approach, called distributed arrival time controller (DATC), to manage arrival times of parts using an integral controller. In this paper, we first review and investigate unique dynamic characteristics of the DATC in regards to convergence and chattering of arrival times. We then propose a new arrival time controller for the DATC that can improve predictability and performance in production scheduling. We call the new mechanism the double integral arrival-time controller (DIAC). We analyse unique characteristics of the DIAC such as oscillatory trajectory of arrival times, their oscillation frequency, and sequence visiting mechanism. In addition, we compare scheduling performance of the DIAC to the existing DATC model through computational experiments. The results show that the proposed system can be used as a mathematical and simulation model for designing adaptable manufacturing systems in the future.     

Sustainable production of bioparaffins in a crude oil refinery

Most prevalent fuels of diesel engine vehicles are the gas oils produced on crude oil bases. According to some disadvantages of fatty acid-methyl-esthers (biodiesels), bioparaffins (mainly isoparaffins) are able to substitute them partially or totally. The production of bioparaffins can be carried out on a wide raw material base. This means the natural triglycerides (different origin non-food vegetable oils, 'brown fat' of sewage works, fat of protein processing, algae oils, etc.), lignocellulose etc., In this paper catalysts (NiMo/Al₂O₃; Pt/SAPO-11; Pt/AlSBA-15, Pt/β-zeolite) for the production of bioparaffins from different natural triglycerides (oils and fats) and high-molecular weight Fischer–Tropsch (heavy; >C₂₂) hydrocarbons (produced from biobased synthesis gas) are introduced. After the proper pretreatment of natural triglyceride feedstocks the suggested two-step technologies (deoxygenation and isomerisation). These are able to produce n- and isoparaffins with yield that approaches the 93–99 % of the theoretical value. Gas oil (diesel fuel) and base oil with high isoparaffin content (≥70 %) can be obtained with simultaneous isomerisation and hydrocracking of Fischer–Tropsch heavy paraffins. Properties of the two diesel fuels (bioparaffin fractions) produced with these methods satisfy the requirements of EN 590:2013 standard. Their cetane number is in the range of 65–75, which makes it possible to use itself and to blend lower quality blending components in higher quantity, which is the source of significant profit increase. The integration possibilities of the suggested technologies into crude oil refineries are introduced, too.     

Integrated multi-factory production and distribution scheduling applying vehicle routing approach

This paper introduces a new integrated multi-factory production and distribution scheduling problem in supply chain management. This supply chain consists of a number of factories joined together in a network configuration. The factories produce intermediate or finished products and supply them to other factories or to end customers that are distributed in various geographical zones. The problem consists of finding a production schedule together with a vehicle routing solution simultaneously to minimise the sum of tardiness cost and transportation cost. A mixed-integer programming model is developed to tackle the small-sized problems using CPLEX, optimally. Due to the NP-hardness, to deal with medium- and large-sized instances, this paper develops a novel Improved Imperialist Competitive Algorithm (IICA) employing a local search based on simulated annealing algorithm. Performance of the proposed IICA is compared with the optimal solution and also with four variants of population-based metaheuristics: Imperialist Competitive Algorithm, Genetic Algorithm, Particle Swarm Optimisation (PSO), and Improved PSO. Based on the computational results, it is statistically shown that quality of the IICA’s solutions is the same as optimal ones solving small problems. It also outperforms other algorithms in finding near-optimal solutions dealing with medium and large instances in a reasonably short running time.     

An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production

Energy-efficient scheduling is highly necessary for energy-intensive industries, such as glass, mould or chemical production. Inspired by a real-world glass-ceramics production process, this paper investigates a bi-criteria energy-efficient two-stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time-of-use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented ε-constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem-tailored constructive heuristic method with local search strategy, a bi-objective tabu search algorithm and a bi-objective ant colony optimisation algorithm are developed to deal with medium- and large-scale problems. Extensive computational experiments are conducted, and a real-world case is solved. The results show effectiveness of the proposed methods, in particular the bi-objective tabu search.     

A new approach to finite scheduling

This paper discusses the general framework of a methodology for material planning and operations scheduling. The methodology is designed to individually schedule customer orders according to the relative priority values assigned to each order, based on various factors including but not limited to due-dates. Resource constraints are considered during the scheduling process to ensure the feasibility of the finite production schedule, while attempting to ensure a reduced production lead time. The methodology is exemplified through test problems compared with the normal approaches. The preliminary results are quite promising, although further mathematical proofs are required to establish the potential advantages of the method in a generic form.     

Lagrangean relaxation approach to joint optimization for production planning and scheduling of synchronous assembly lines

This paper focuses on simultaneous optimisation of production planning and scheduling problem over a time period for synchronous assembly lines. Differing from traditional top-down approaches, a mixed integer programming model which jointly considers production planning and detailed scheduling constraints is formulated, and a Lagrangian relaxation method is developed for the proposed model, whereby the integrated problem is decomposed into planning, batch sequencing, tardiness and earliness sub-problems. The scheduling sub-problem is modelled as a time-dependent travelling salesman problem, which is solved using a dynasearch algorithm. A proposition of Lagrangian multipliers is established to accelerate the convergence speed of the proposed algorithm. The average direction strategy is employed to solve the Lagrangian dual problem. Test results demonstrate that the proposed model and algorithm are effective and efficient.     

A genetic algorithm approach for production scheduling with mould maintenance consideration

The traditional approach for maintenance scheduling concerns single-resource (machine) maintenance during production which may not be sufficient to improve production system reliability as a whole. Besides, in the literature many researchers schedule maintenance activities periodically with fixed maintenance duration. However, in a real manufacturing system maintenance activities can be executed earlier and the maintenance duration will become shorter since less time and effort are required. A practical example is that in a plastic production system, the proportion of machine-related downtime is even lower than mould-related downtime. The planned production operations are usually interrupted seriously because of the mismatch among the maintenance periods between injection machine and mould. In this connection, this paper proposes to jointly schedule production and maintenance tasks of multi-resources in order to improve production system reliability by reducing the mismatch among various processes. To integrate machine and mould maintenance tasks in production, this paper attempts to model the production scheduling with mould scheduling (PS-MS) problem with time-dependent deteriorating maintenance schemes. The objective of this paper is to propose a genetic algorithm approach to schedule maintenance tasks jointly with production jobs for the PS-MS problem, so as to minimise the makespan of production jobs.