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Abstract Today’s business environment involves a globalised market, greater than before competition and more challenging customers, all factors which contribute to higher uncertainty and variability. Manufacturing flexibility is becoming more important in order to cope with the complexity of products through frequency volume changes and evaluations of the technological requirements of products. The research for this thesis was performed within a subcontractor company, Laserkraft AB, who focus on laser cutting, turning and welding processes in their production. The company utilises a variety of volume and product mixes, which is in correlation with the objective of this study. The purpose of this research was to investigate the common source drivers in order to achieve volume and product mix flexibility on batch production systems. First, a literature review was conducted in order to build the framework of common source factors between volume and product mix flexibility. Then, a single case study was conducted to examine the outcomes of framework on batch production. In this case, qualitative techniques included interviews and an observation of the shop floor. The analysis of this study was conducted with empirical research on a case study and theoretical framework from literature. From the literature stand point; it was found that flexible manufacturing competencies (FMC) and strategic flexibility approaches are two main elements to determine internal source drivers between volume and product mix flexibility. The groups of common source factors were then analysed with respect to characteristics of batch production systems at the chosen company. A comparison between the framework and the empirical findings identified source drivers in order to achieve volume and product mix flexibility. Due to the limited nature of the study, all source factors that have an impact on achieving volume and product mix flexibility might not be presented in this thesis. Besides, it is difficult to generalise the result on a single case study. As a result, each organisation and industry refers to their product, process and type of layout, and requires a group of practices to achieve volume and product mix flexibility. This thesis concludes with the top three common source factors between volume and product mix flexibility such as: set-up time reduction, multi-trained employees and advanced manufacturing technology.

The focuses of this dissertation are problems of batch production scheduling problems for perishable products with setup times, with the main applications in answering production planning problems faced by manufacturers of perishable products, such as beers, vaccines and yoghurts. The benefits of effective production plans can help companies reduce their total costs substantially to gain the competitive advantages without reduction of the service level in a globalize economy. We develop concepts and methodologies that are applied in two fundamental problems: (i) the batch production scheduling problem for perishable products with sequence-independent setup times (BPP-SI) and (ii) the batch production scheduling problem for perishable products with sequence-dependent setup times (BPP-SD). The problem is that given a set of forecast demand for perishables products to be produced by a set of parallel machines in the single stage of batch production, with each product having fixed shelf-life times and each machine requiring setup times before producing a batch of product, find the master production schedule which minimizes total cost over a specified time horizon. We present the new models for both problems by formulating them as a Mixed Integer Program (MIP) on the discrete time. Computational studies in BPP-SI and BPP-SD for industrial problems are presented. In order to efficiently solve the large BPP-SI problems in practice, we develop the five efficient heuristics. The extensive computational results show that the developed heuristics can obtain the good solution for the very large problem size and require very short amount of computational time.

To improve product quality and reduce cost, batch production is often implemented in many exible manufacturing systems. However, the current literature does not provide any method to analyze the quality performance in a flexible manufacturing system with batch production. In this research, we present an analytical method with closed-form formula to evaluate the quality performance in such systems. Based on the model, we discover and investigate monotonic and non-monotonic properties in quality to provide practical guidance for operation management. To improve product quality, we introduce the notions of quality improvability with respect to product sequencing. In addition, we develop the indicators for quality improvability based on the data available on the factory floor rather than complicated calculations. We define the bottleneck sequence and bottleneck transition as the ones that impede quality in the strongest manner, investigate the sensitivity of quality performance with respect to sequences and transitions, and propose quality bottleneck sequence and transition indicators based on the measured data. Finally, we provide a case study at an automotive paint shop to show how this method is applied to improve paint quality. Moreover, we explore a potential application to reduce energy consumption and atmospheric emissions at automotive paint shops. By selecting appropriate batch and sequence policies, the paint quality can be improved and repaints can be reduced so that less material and energy will be consumed, and less atmospheric emissions will be generated. It is shown that such scheduling and control method can lead to significant energy savings and emission reduction with no extra investment nor changes to existing painting processes. The successful development of such method would open up a new area in manufacturing systems research and contribute to establish a solid foundation for an integrated study on productivity, quality and exibility. In addition, it will provide production engineers and operation managers a quantitative tool for continuous improvement on product quality in flexible manufacturing environment

This research is concerned with the development of efficient solutions to various problems that arise in the flow-shop environments which utilize lot-streaming. Lot streaming is a commonly used process of splitting production lots into sublots and, then, of scheduling the sublots in an overlapping fashion on the machines, so as to expedite the progress of orders in production and to improve the overall performance of the production system. The different lot-streaming problems that arise in various flow-shop environments have been divided into two categories, single-lot problems and multiple-lot problems. Further classification of the multiple-lot problems into the lot streaming sequencing problem (LSSP) and the flow-shop lot-streaming (FSLS) problem is made in this work. This classification is motivated by the occurrence of these problems in the industry. Several variants of these problems are addressed in this research. In agreement with numerous practical applications, we assume sublots of equal sizes. It turns out that this restriction paves the way to the relaxation of several typical limitations of current lot-streaming models, such as assumption of negligible transfer and setup times or consideration of only the makespan criterion. For the single-lot problem, a goal programming (GP) approach is utilized to solve the problem for a unified cost objective function comprising of the makespan, the mean flow time, the average work-in-process (WIP), and the setup and handling related costs. A very fast optimal solution algorithm is proposed for finding the optimal number of sublots (and, consequently, the sublot size) for this unified cost objective function in a general m-machine flow shop. For the more complicated multiple-lot problem, a near-optimal heuristic for the solution of the LSSP is developed. This proposed heuristic procedure, referred to as the Bottleneck Minimal Idleness (BMI) heuristic, identifies and employs certain properties of the problem that are irregular in traditional flow-shop problems, particularly the fact that the sublot sizes eminating from the same lot type and their processing times (on the same machines) are identical. The BMI heuristic attempts to maximize the time buffer prior to the bottleneck machine, thereby minimizing potential bottleneck idleness, while also looking-ahead to sequence the lots with large remaining process time earlier in the schedule. A detailed experimental study is performed to show that the BMI heuristic outperforms the Fast Insertion Heuristic (the best known heuristic for flow-shop scheduling), when modified for Lot Streaming (FIHLS) and applied to the problem on hand. For the FSLS problem, several algorithms are developed. For the two-machine FSLS problem with an identical sublot-size for all the lots, an optimal pseudo-polynomial solution algorithm is proposed. For all practical purposes (i.e., even for very large lot sizes), this algorithm is very fast. For the case in which the sublot-sizes are lot-based, optimal and heuristic procedures are developed. The heuristic procedure is developed to reduce the complexity of the optimal solution algorithm. It consists of a construction phase and an improvement phase. In the construction phase, it attempts to find a near-optimal sequence for the lots and then, in the improvement phase, given the sequence, it attempts to optimize the lot-based sublot-sizes of each of the lots. Extensions of the solution procedures are proposed for the general m-machine FSLS problem. A comprehensive simulation study of a flow shop system under lot streaming is conducted to support the validity of the results and to demonstrate the effectiveness of the heuristic procedures. This study clearly indicates that, even in dynamic practical situations, the BMI rule, which is based on the proposed BMI heuristic, outperforms existing WIP rules, commonly used in industry, in scheduling a flow-shop that utilizes lot streaming. With respect to the primary performance measure - cycle time (or MFT) - the BMI rule demonstrates a clear improvement over other WIP rules. It is further shown that it also outperforms other WIP rules with respect to the output variability measure, another important measure in flow-shop systems. The effects of several other factors, namely system randomness, system loading, and bottleneck-related (location and number), in a flow-shop under lot streaming, are also reported. / Ph. D.

The aim of this work is to create a methodology for creating a strategy to increase the level of automation of manufacturing process. Based on the customer´s requirements, management of manufacturing company, the concept of methodology was developed. The research and design of the necessary tools and procedures to evaluate the feasibility of automation were subsequently carried out. Based on the outputs from the feasibility analysis, rules for the formulation of the automation strategy were established. The method was subsequently applied to the process of the manufacturing company for which an analysis of the feasibility of automation was carried out. Subsequently, recommendations were made for further steps to increase the level of automation, thus proposing a strategy for the company. The methodology created is applicable to companies with discrete batch production that do not have defined the automation strategy yet.

This master’s thesis named Continuous/batch production in environment Industry 4.0 deals with software and principles that are designed for discrete manufacturing and their application to the continuous and batch production. First, the functions and properties of individual programs for discrete manufacturing were descripted, then this acquired knowledge was related to continuous and batch production. On the basis of the gained knowledge, a program for the processing of liquid materials with using two tanks was created. This program is aimed at customizing of the final product.

Indiana University-Purdue University Indianapolis (IUPUI) / A foreign concept to most twenty-first century individuals, a saddletree provides support and acts as the framework to saddles, giving saddlers a base on which to add cushioning, stretch leather, and create beautiful or functional saddles. Saddletree factories were an integral part of Madison, Indiana’s late nineteenth-century economy. As one of the Ohio River town’s leading industries, saddletree shops employed approximately 125 men during 1879, Madison’s peak saddletree production year, and made Madison a national center of saddletree production. However, the industry faded into oblivion as the beginning of the twentieth century, leaving the men drawn to these shops in the 1870s and 1880s to find new opportunities. While past historians contributed to the fields of industrial and economic history by studying large industries engaged in mass production in major urban areas, Madison’s saddletree workers represent a view of nineteenth-century specialized production. This thesis examines the saddletree industry’s place in Madison during the late nineteenth century and the lives of saddletree workers during and after the industry’s peak. My findings, based off extensive digital research and tools utilized in earlier social mobility studies, create a nuanced view of Madison’s relationship to the saddletree industry, saddletree makers, and what the industry’s collapse meant to saddletree factory employees.