Integration of demand management and production planning in a batch process manufacturing system: Case study

Production Planning;Batch Production;production

A Multi-Objective Optimization Approach for Multi-Head Beam-Type Placement Machines

This paper addresses a highly challenging scheduling problem in the field of printed circuit board (PCB) assembly systems using Surface Mounting Devices (SMD). After describing some challenging optimization sub-problems relating to the heads of multi-head surface mounting placement machines, we formulate an integrated multi-objective mathematical model considering of two main sub-problems simultaneously. The proposed model is a mixed integer nonlinear programming one which is very complex to be solved optimally. Therefore, it is first converted into a linearized model and then solved using an efficient multi-objective approach, i.e., the augmented epsilon constraint method. An illustrative example is also provided to show the usefulness and applicability of the proposed model and solution method.PCB assembly. Multi-head beam-type placement machine. Multi-objective mathematical programming. Augmented epsilon-constraint method

Computer integrated manufacturing in the chemical industry: Theory & practice

This paper addresses the possibilities of implementing Computer Integrated Manufacturing in the process industry, and the chemical industry in particular. After presenting some distinct differences of the process industry in relation to discrete manufacturing, a number of focal points are discussed. They identify the adaptations to be made to a conventional CIM system, so that it will be applicable to the process industry. Interviews with managers of six chemical firms indicate that the process industry may benefit from a new CIM approach to management thinking.Chemical Industry;Manufacturing;CIM;production

Amendment of Heuts-Selen's lotsizing and sequencing heuristic for single stage process manufacturing systems

Productivity;Production Scheduling;Manufacturing;production

Determinants of Informal Coordination in Networked Supply Chains

Purpose – Provide insight into the determinants or constructs that enable informally networked supply chains to operate in order to achieve improved operational performance. Design/methodology/approach – The research is based on a wide literature review, focused on the identification of dimensions of informal networking in supply chains along network connectivity, supply chain relationship alignment, informally networked supply chain, and operational performance. These determinants or constructs of informal networking were statistically validated for validity and reliability, using a sample of 231 supply chain professionals. Findings – Four determinant of informal networking were derived: capability connectivity, describing the ability of supply chain partners to rapidly and informally integrate capabilities to service an ad hoc market requirement; relationship alignment or the ability to informally integrate resources across supply chain partners in the context of highly dynamic market situations; the informally networked supply chain itself, measuring the ability of supply chain partners to respond to transient opportunities in the context of highly dynamic markets; and finally operational performance which measures the effect informal networking has on company performance. Research limitations/implications – Future research may investigate the effects of informally networked supply chains on a broader array of measures of company performance, and additional measures of operational performance. Practical implications – These newly developed constructs or determinants give managers further insight into which dimensions need to be fostered to enable informally networked supply chains to operate, and what operational gains may be potentially realised as a result of informal networking. Originality/value – This paper contributes to enhancing the understanding of the newly emerging phenomenon of informal networking in supply chains and how it may yield operational efficiency and effectiveness gains.construct development;coordination;informal networking;supply chain

An Aggregated Optimization Model for Multi-Head SMD Placements

In this article we propose an aggregate optimization approach by formulating the multi-head SMD placement optimization problem into a mixed integer program (MIP) with the variables based on batches of components. This MIP is tractable and effective in balancing workload among placement heads, minimizing the number of nozzle exchanges, and improving handling class. The handling class which specifies the traveling speed of the robot arm, to the best of our knowledge, has been for the first time incorporated in an optimization model. While the MIP produces an optimal planning for batches of components, a new sequencing heuristics is developed in order to determine the final sequence of component placements based on the outputs of the MIP. This two-stage approach guarantees a good feasible solution to the multi-head SMD placement optimization problem. The computational performance is examined using real industrial data.Multi-head surface mounting device;Component placement;Variable placement speed

A production model and maintenance planning model for the process industry

In this paper a model is developed to simultaneously plan preventive maintenance and production in a process industry environment, where maintenance planning is extremely important. The model schedules production jobs and preventive maintenance jobs, while minimizing costs associated with production, backorders, corrective maintenance and preventive maintenance. The formulation of the model is flexible, so that it can be adapted to several production situations. The performance of the model is discussed and alternate solution procedures are suggested.Production Models;Maintenance;production

Blending modelling in a process manufacturing system

integer programming;manufacturing;blending;production

Application of mixed integer programming to a large scale logistics problem

Integer Programming;Logistics;production

Strategic marketing, production, and distribution planning of an integrated manufacturing system

Production Scheduling;Distribution;CIM;production