Multi-product cost and value stream modelling in support of business process analysis

To remain competitive, most Manufacturing Enterprises (MEs) need cost effective and responsive business processes with capability to realise multiple value streams specified by changes in customer needs. To achieve this, there is the need to provide reusable computational representations of organisational structures, processes, information, resources and related cost and value flows especially in enterprises realizing multiple products. Current best process mapping techniques do not suitably capture attributes of MEs and their systems and thus dynamics associated with multi-product flows which impact on cost and value generation cannot be effectively modelled and used as basis for decision making. Therefore, this study has developed an integrated multiproduct dynamic cost and value stream modelling technique with the embedded capability of capturing aspects of dynamics associated with multiple product realization in MEs. The integrated multiproduct dynamic cost and value stream modelling technique rests on well experimented technologies in the domains of process mapping, enterprise modelling, system dynamics and discrete event simulation modelling. The applicability of the modelling technique was tested in four case study scenarios. The results generated out of the application of the modelling technique in solving key problems in case study companies, showed that the derived technique offers better solutions in designing, analysing, estimating cost and values and improving processes required for the realization of multiple products in MEs, when compared with current lean based value stream mapping techniques. Also the developed technique provides new modelling constructs which best describe process entities, variables and business indicators in support of enterprise systems design and business process (re) engineering. In addition to these benefits, an enriched approach for translating qualitative causal loop models into quantitative simulation models for parametric analysis of the impact of dynamic entities on processes has been introduced. Further work related to this research will include the extension of the technique to capture relevant strategic and tactical processes for in-depth analysis and improvements. Also further research related to the application of the dynamic producer unit concept in the design of MEs will be required

INTEGRATED COMPUTER-AIDED DESIGN, EXPERIMENTATION, AND OPTIMIZATION APPROACH FOR PEROVSKITES AND PETROLEUM PACKAGING PROCESSES

According to the World Economic Forum report, the U.S. currently has an energy efficiency of just 30%, thus illustrating the potential scope and need for efficiency enhancement and waste minimization. In the U.S. energy sector, petroleum and solar energy are the two key pillars that have the potential to create research opportunities for transition to a cleaner, greener, and sustainable future. In this research endeavor, the focus is on two pivotal areas: (i) Computer-aided perovskite solar cell synthesis; and (ii) Optimization of flow processes through multiproduct petroleum pipelines. In the area of perovskite synthesis, the emphasis is on the enhancement of structural stability, lower costs, and sustainability. Utilizing modeling and optimization methods for computer-aided molecular design (CAMD), efficient, sustainable, less toxic, and economically viable alternatives to conventional lead-based perovskites are obtained. In the second area of optimization of flow processes through multiproduct petroleum pipelines, an actual industrial-scale operation for packaging multiple lube-oil blends is studied. Through an integrated approach of experimental characterization, process design, procedural improvements, testing protocols, control mechanisms, mathematical modeling, and optimization, the limitations of traditional packaging operations are identified, and innovative operational paradigms and strategies are developed by incorporating methods from process systems engineering and data-driven approaches

Integrated Location-Production-Distribution Planning in a Multiproducts Supply Chain Network Design Model

This paper proposes integrated location, production, and distribution planning for the supply chain network design which focuses on selecting the appropriate locations to build a new plant and distribution center while deciding the production and distribution of the product. We examine a multiechelon supply chain that includes suppliers, plants, and distribution centers and develop a mathematical model that aims at minimizing the total cost of the supply chain. In particular, the mathematical model considers the decision of how many plants and distribution centers to open and where to open them, as well as the allocation in each echelon. The LINGO software is used to solve the model for some problem cases. The study conducts various numerical experiments to illustrate the applicability of the developed model. Results show that, in small and medium size of problem, the optimal solution can be found using this solver. Sensitivity analysis is also conducted and shows that customer demand parameter has the greatest impact on the optimal solution

Multiproduct supplye chain analysis through by simulation with kanban and EOQ system

This work reviews lean literature on the supply chain focused on the operational approach, from the lean management to the Kanban system. But, the main issue of this work is to analyze the behavior of a lean supply chain using a Kanban system managing the planning in two different ways. The difference between both is related to the production order or sequence to follow: the product with fewer inventories in stock (the most critical to run out) or the one which requires less set-up time to optimize unproductive times. The study the behavior of the supply chain, it would be done through simulation with many different scenarios: 5 different demands, each one with two coefficients of variance, 4 different batch sizes, 4 different compositions of production and process saturation and ensuring different service levels between 92% and 98%. To compare these supply chain models, an approach of the supply chain using the EOQ (Economic Order Quantity) system will be also simulated in the same conditions but with one batch size, the most economic one

Combined make-to-order and make-to-stock in a food production system

The research into multi-product production/inventory control systems has mainly assumed one of the two strategies: Make-to-Order (MTO) or Make-to-Stock (MTS). In practice, however, many companies cater to an increasing variety of products with varying logistical demands (e.g. short due dates, specific products) and production characteristics (e.g. capacity usage, setup) to different market segments and so they are moving to more MTO-production. As a consequence they operate under a hybrid MTO-MTS strategy. Important issues arising out of such situations are, for example, which products should be manufactured to stock and which ones on order and, how to allocate capacity among various MTO-MTS products. This paper presents the state-of-the-art literature review of the combined MTO-MTS production situations. A variety of production management issues in the context of food processing companies, where combined MTO-MTS production is quite common, are discussed in details. The authors propose a comprehensive hierarchical planning framework that covers the important production management decisions to serve as a starting point for evaluation and further research on the planning system for MTO-MTS situations.

Allocating work in process in a multiple-product CONWIP system with lost sales

To operate a multiple-product manufacturing system under a CONWIP control policy, one must decide how to assign kanbans to products. With a fixed total number of kanbans in a competitive environment, the goal is to determine their allocation to product types in order to minimize lost sales equitably. In particular, we consider systems in which the products may make multiple visits to the same station with a different processing time distribution on each repeat visit. With a fixed number of kanbans dedicated to each product, the system is modeled as a multiple-chain multiple-class closed queuing network. A nonlinear program simultaneously provides an approximate performance evaluation and optimizes the allocation of kanbans to product types. In numerical examples, the allocations identified are similar to those obtained by exhaustive enumeration with simulation, but frequently differ significantly from a naïve allocation according to demand rates. A variant of the model that minimizes the total work-in-process to achieve specified throughput targets yields results similar to a previous heuristic method

Satisfying multiproduct demand with a FPR-based inventory system featuring expedited rate and scraps

Facing stiff competition in worldwide markets, capability of meeting timely demands of multiproduct and satisfying customer’s desired product quality are essential to present-day manufacturers. Motivated by achieving the aforementioned goals, this research intends to find most economic common cycle length for a multiproduct finite production rate (FPR)-based inventory system, wherein, imperfect production process with expedited fabrication rate and random scrap is assumed. Extra setup and unit costs are associated with the adjusted rate, and imperfect products are screened and scrapped. A mathematical model is cautiously constructed to examine and resolve the problem. A numerical illustration is employed to exhibit the applicability of the proposed method. Except finding the most economic common cycle time for the problem, core contribution of this study also is associated with the individual and combined impact(s) of important factors to the problem, and hence, enabling management of manufacturing firms to make efficient/cost-effective decision and gain competitive advantages

Economic evaluation in decision models: a critical review and methodological propositions

International audienceDecision models of industrial management articles are often based on an economic criterion to find the proposed solution. They use economic parameters that are generally imported from the firm cost accounting system. When cost information is not adapted to the decision, the obtained solution of the model may be invalid. In this article, we deal with a critical literature review to report the methodological problems encountered in industrial management articles vis-à-vis the used costs. Finally we suggest methodological propositions to be kept in mind by authors when they are using costs in decision models

The integrated use of enterprise and system dynamics modelling techniques in support of business decisions

Enterprise modelling techniques support business process re-engineering by capturing existing processes and based on perceived outputs, support the design of future process models capable of meeting enterprise requirements. System dynamics modelling tools on the other hand are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of enterprise and system dynamics modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise during the production of composite bearings. The case study testing reported has led to the specification of a new modelling methodology for analysing and managing dynamics and complexities in production systems. This methodology is based on a systematic transformation process, which synergises the use of a selection of public domain enterprise modelling, causal loop and continuous simulationmodelling techniques. The success of the modelling process defined relies on the creation of useful CIMOSA process models which are then converted to causal loops. The causal loop models are then structured and translated to equivalent dynamic simulation models using the proprietary continuous simulation modelling tool iThink

Global supply chains of high value low volume products

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