A Simulation Approach for Performance Measures of Food Manufacturing Process

In Malaysia, Small and Medium-sized Enterprise (SME) of food manufacturing industry is the second highest contributor in manufacturing sector and plays an important role to the economic development and growth. Hence, monitoring process of the industry should be occupied comprehensively and appropriately even though it is categorized under small- scale organization. Shrimp paste production is one of the small-scale food production that is popular in Malaysia. In this study, a performance of shrimp paste production is measured by using simulation approach. A discrete event simulation model is developed to illustrate the processes in the production line which involved four major processes. From the model, it is estimated that the average process time taken to produce 2000 pieces of shrimp paste is 235.13 minutes while the average waiting time taken in the operation system is 89.21 minutes. The findings also show that the bottleneck of the production process is found to be at packaging process and some of the resources are not fully utilized

Design of sustainable industrial systems by integrated modeling of factory building and manufacturing processes

This paper presents an integrated approach that combines ‘Sustainable Building Design’ tools and ‘Sustainable Manufacturing Process’ tools to create a tool for the design of sustainable manufacturing systems.’ Currently no such integrated tools are in use by manufacturers to assess energy performance, identify improvement areas and help suggest actions. This paper describes the development of a tool that through such integrated modelling can help identify improvements via its library of tactics. These sustainable manufacturing tactics have to account for location and time, as well as production process, in a manner that is not currently supported by either manufacturing process simulation tools, or building energy tools. Through case study applications, the integrated modelling of real world industrial processes is demonstrated, from target and boundary settings, mapping (manufacturing process systems, material flow, surrounding buildings and facilities), data collection, simulation, improvement opportunities and optimisation

Thermal modelling of manufacturing processes and HVAC systems

The two main energy consumers within a manufacturing plant are the HVAC systems and manufacturing processes. Studies have predominately looked at energy demand associated with manufacturing a single product or a production line, as well as analysis of energy use within a building, but little work has investigated the interaction between manufacturing processes and the surrounding building. Dynamic time based building energy simulation was used to determine the thermal behaviour of the manufacturing facility. The study establishes the importance of analysing manufacturing energy flows alongside that of the building in order to capture all thermal and energy flows. The relationship between the energy demand of HVAC systems with manufacturing productivity is determined. The use of the current degree-day method of building analysis was proven inappropriate for manufacturing facilities, due to such significant heat gains from manufacturing equipment, and impact of equipment on indoor conditions. The need for a proactive HVAC system based on manufacturing demand is introduced, allowing for control of the environment prior to significant temperature or humidity changes

Otimização do processo de produção de gelo em lojas de retalho alimentar

Este estudo foi desenvolvido no âmbito da Unidade curricular de Dissertação /Projeto / Estágio do Mestrado em Engenharia Mecânica – Ramo de Gestão Industrial, do Instituto Superior de Engenharia do Porto. O projeto foi desenvolvido no Departamento de Controlo de Custos na empresa SONAE MC, que atua no setor do retalho alimentar, com o objetivo de reduzir os custos energéticos associados à produção de gelo, destinado à conservação de artigos piscículos expostos em loja e na retaguarda, assim como do respetivo processo de degelo que ocorre no fim de cada dia de trabalho. A abordagem passou, inicialmente, pela recolha e análise de dados relativos a consumos de água e energia dos equipamentos de produção de gelo, e à relação desses consumos com alguns indicadores de negócio, com o objetivo de uniformizar parâmetros como a quantidade de gelo utilizado. Numa fase posterior foi desenvolvido um modelo de otimização, com recurso a um modelo de programação linear inteira, com o objetivo de planear os períodos de funcionamento das máquinas de gelo, tendo em consideração a variação de tarifa energética que ocorre durante o dia, minimizando assim os custos associados à produção de gelo. A implementação do modelo a um conjunto de lojas, para efeito de teste, revelou uma redução de cerca de 35% dos custos energéticos, assim como uma melhoria na qualidade do gelo através do planeamento da produção o mais próximo possível do momento de necessidade, diminuindo o efeito de aglomeração causado pelo tempo de armazenamento excessivo.This study was developed within the course of Thesis / Project / Internship of the Master Degree in Mechanical Engineering – Industrial Management branch from the Polytechnic School of Engineering, in Porto. The project was developed in the Cost Control Department at SONAE MC, a leader in the food retail business in Portugal. The goal was to reduce the energy costs of the ice production process used to preserve fresh fish displayed on shelves and stored in boxes at the background of the store, and the respective melting of the ice at the end of each day. The approach started with the data analysis of water and energy consumption of the ice production units, and the relation between those consumptions with some business performance indicators, with the purpose of standardize parameters such as the ice quantities used in shelve. Then, an integer linear model was proposed with the objective of reducing the total energy costs associated with the ice production process, by scheduling the production considering the energy tariffs variation during the day. The implementation of the model to a group of stores revealed a 35% reduction in the energy costs, and also a significant improvement in the quality of the ice, by scheduling the production as late as possible, reducing the effect of ice agglomeration caused by excessive storage times

Energy Sustainability in Changeable Manufacturing Systems

University of Minnesota M.S.E.M. thesis. October 2017. Major: Engineering Management. Advisor: Tarek AlGeddawy. 1 computer file (PDF); vi, 76 pages.In a dynamic production environment, not only the product portfolio and demands are varying throughout a multi-period horizon, but also the economic aspects of the environment, such as energy pricing, change with time. The thesis of this work states that energy price fluctuation has a considerable optimizable effect on manufacturing system structural and operational decisions. This work progressively presents three novel linear mathematical models to optimize that effect. In the first step, a novel basic linear mixed integer mathematical model is proposed to maximize the sustainability of changeable manufacturing systems (MSCM) on the operational level. The model focuses on three factors, which are the change pattern in energy prices throughout the day, the transportation cost of jobs between machines, and the setup cost of each machine, which is dependent on the job sequence. The model output is a system configuration plan, indicating arrangement of machines in the system, and the sequence of jobs, which need to be produced on one day. It is solved by CPLEX solver in GAMS software for nine different problem sizes. The new LMI model finds the optimum configuration plan and job sequence in a reasonable time, which illustrates the efficiency and practicality of the proposed model. In the second step, a new linear mathematical model is presented to maximize the sustainability of changeable manufacturing systems on the structural level (MSSCM) by selecting the layout reconfiguration and material handling system in each period. It is solved by CPLEX solver in GAMS software to analyze influence of energy pricing and demand fluctuation on system convertibility and scalability, which can affect layout configuration selection. In the last step, a novel mixed integer linear mathematical model (MILTEC) is presented to maximize the sustainability of RMS on both the structural and operational levels. The system configuration planning in each period of time consists of machines layout and task scheduling which are the most interrelated decisions on the system level. The novel aspect of the presented model is the consideration of energy sustainability concurrently with system configuration and task scheduling decisions in a changing manufacturing environment. The model objective is to minimize total costs of energy consumption, system reconfiguration throughout the planning horizon, and part transportation between machines, which all depend on fluctuations in energy pricing and demand during different periods of time. Several case studies are solved by GAMS Software using the branch-and-bound technique to illustrate the performance of the presented model and analyze its sensitivity to the volatility of energy pricing and demand and their effect on system changeability. An efficient genetic algorithm (GA) has been developed to solve the proposed model in larger scale due to its NP-hardness (non-deterministic polynomial-time hardness). The results are compared to GAMS to validate the developed GA. It shows that the proposed GA finds near-optimal solutions in 70% shorter time than GAMS on average. Different examples are also solved resulting in negligible differences between solutions in several runs of each example to verify the efficiency of the proposed GA

Sustainable manufacturing tactics and improvement methodology : a structured and systematic approach to identify improvement opportunities

Growing environmental concerns caused by increasing consumption of natural resources and pollution need to be addressed. Manufacturing dictates the efficiency with which resource inputs are transformed into economically valuable outputs in the form of products and services. Consequently it is also responsible for the resulting waste and pollution generated from this transformation process. This research explored the challenges faced by sustainable manufacturing as a concept and as a model for manufacturing systems. The work is strongly based on the concepts of sustainability and industrial ecology applied at factory level. The research objectives were to understand what companies are doing to improve their sustainability performance at operational level (resource productivity) and to help other companies repeating such improvements in their own factory. In other words, the aim is to generalise sustainable practices across the manufacturing industry. The work started with a review of existing theories and practices for sustainable manufacturing and other related fields of research such as industrial ecology, cleaner production and pollution prevention. The concepts, themes, strategies and principles found in the literature provided a strong foundation to approach resource productivity improvements. The industrial cases collected gave an insight into the application of these strategies and principles in a factory. From the analysis of existing theories and practices, generic tactics were developed by translating 1000+ practices into generic rules and by mapping them against strategies and principles for sustainable manufacturing to check the completeness and consistency of the tactics library. To test the tactics and assist the user in their use through factory modelling, an improvement methodology was developed based on the same strategies and principles to provide a structured guide for accessing tactics and systematically identifying improvement opportunities. The research findings were tested with a series of prototype applications. These tests were carried out as part of a wider project (THERM). This project uses a modelling and simulation approach to capture the resource flows (material, energy, water and waste), the interactions within the manufacturing system (manufacturing operations, surrounding buildings and supporting facilities) and the influence of external factors‘ variation (weather conditions, building orientation and neighbouring infrastructures). The outcomes of the prototype applications helped develop and refine the research findings. The contribution to knowledge of this research resides in bridging the gap between high-level concepts for sustainability and industrial practices by developing a library of tactics to generalise sustainable manufacturing practices and an improvement methodology to guide the tactics implementation. From a practical viewpoint, the research provides a structured and systematic approach for manufacturers to undertake the journey towards more sustainable practice by improving resource flows in their factory