Multi-objective optimization of product variety and manufacturing complexity in mixed-model assembly systems

Product variety has increased dramatically as manufacturers compete for market shares. While higher variety of products may satisfy a broader range of customers, it also introduces complexity in manufacturing. A multi-objective optimization approach is proposed to balance product variety and manufacturing complexity when designing a product family and the mixed-model assembly system. Relative complexity is introduced to measure the complexity and to find the best set of product variants to be offered while balancing market share and complexity. Numerical examples are provided to demonstrate the approach.     

Monoid-labeled transition systems

Given a -complete (semi)lattice , we consider -labeled transition systems as coalgebras of a functor ⁽⁻⁾, associating with a set X the set ^X of all -fuzzy subsets. We describe simulations and bisimulations of -coalgebras to show that L⁽⁻⁾ weakly preserves nonempty kernel pairs iff it weakly preserves nonempty pullbacks iff L is join infinitely distributive (JID).Exchanging for a commutative monoid , we consider the functor ⁽⁻⁾_ω which associates with a set X all finite multisets containing elements of X with multiplicities m M. The corresponding functor weakly preserves nonempty pullbacks along injectives iff 0 is the only invertible element of , and it preserves nonempty kernel pairs iff is refinable, in the sense that two sum representations of the same value, r₁ + … + r_m = c₁ + … + c_n, have a common refinement matrix (m_{(i, j)}) whose k-th row sums to r_k and whose l-th column sums to c_l for any 1≤ k ≤ m and 1 ≤ l ≤ n.     

A model for assessing the layout structural complexity of manufacturing systems

The layout of a manufacturing facility/system not only shapes its material flow pattern and influence transportation and operation cost, but also affects logistics and parts/machine assignment decisions. The layout of manufacturing systems determines its structural complexity by virtue of its design configuration characteristics. This paper introduces a new model and indices for assessing the structural complexity of manufacturing systems layout in the physical domain. Six complexity indices, based on the physical structural characteristics of the layout, have been introduced and formulated. They are layout density, path, cycle, decision points, redundancy distribution and magnitude indices. An overall Layout Complexity Index (LCI) which combines all indices is developed using a novel method based on radar plots which is insensitive to the order of plotting the individual indices. The use of the developed LCI is demonstrated using six typical types of manufacturing systems layouts and relevant guidelines are presented. The developed model and complexity indices help design system layouts for least complexity and compare layout alternatives that meet the specifications, at early design stages. It supports making trade-off decisions regarding manufacturing systems flexibility and complexity and their associated costs.     

Logic of transition systems

Labeled transition systems are key structures for modeling computation. In this paper, we show how they lend themselves to ordinary logical analysis (without any special new formalisms), by introducing their standard first-order theory. This perspective enables us to raise several basic model-theoretic questions of definability, axiomatization and preservation for various notions of process equivalence found in the computational literature, and answer them using well-known logical techniques (including the Compactness theorem, Saturation and Ehrenfeucht games). Moreover, we consider what happens to this general theory when one restricts attention to special classes of transition systems (in particular, finite ones), as well as extended logical languages (in particular, infinitary first-order logic). We hope that this puts standard logical formalisms on the map as a serious option for a theory of computational processes. As a side benefit, our approach increases comparability with several other existing formalisms over labeled transition systems (such as Process Algebra or Modal Logic). We provide some pointers to this effect, too.     

Design of systems for productivity and well being

It has always been an ambition within the ergonomic profession to ensure that design or redesign of production systems consider both productivity and employee well being, but there are many approaches to how to achieve this. This paper identifies the basic issues to be addressed in light of some research activities at DTU, especially by persons responsible for facilitating design processes. Four main issues must be addressed: (1) determining the limits and scope of the system to be designed; (2) identifying stakeholders related to the system and their role in the system design; (3) handling the process' different types of knowledge; and (4) emphasizing that performance management systems, key performance indicators (KPIs), and leadership are also part of the system design and must be given attention. With the examples presented, we argue that knowledge does exist to help system design facilitators address these basic issues.     

Approximating and computing behavioural distances in probabilistic transition systems

In an earlier paper we presented a pseudometric on the states of a probabilistic transition system, yielding a quantitative notion of behavioural equivalence. The behavioural pseudometric was defined via the terminal coalgebra of a functor based on a metric on Borel probability measures. In the present paper we give a polynomial-time algorithm, based on linear programming, to calculate the distances between states up to a prescribed degree of accuracy.     

Definable transductions and weighted logics for texts

A text is a word together with an additional linear order on it. We study quantitative models for texts, i.e. text series which assign to texts elements of a semiring. We introduce an algebraic notion of recognizability following Reutenauer and Bozapalidis as well as weighted automata for texts combining an automaton model of Lodaya and Weil with a model of Ésik and Németh. After that we show that both formalisms describe the text series definable in a certain fragment of weighted logics as introduced by Droste and Gastin. In order to do so, we study certain definable transductions and show that they are compatible with weighted logics.     

Network thermodynamics and complexity: a transition to relational systems theory.

Most systems of interest in today's world are highly structured and highly interactive. They cannot be reduced to simple components without losing a great deal of their system identity. Network thermodynamics is a marriage of classical and non-equilibrium thermodynamics along with network theory and kinetics to provide a practical framework for handling these systems. The ultimate result of any network thermodynamic model is still a set of state vector equations. But these equations are built in a new informative way so that information about the organization of the system is identifiable in the structure of the equations. The domain of network thermodynamics is all of physical systems theory. By using the powerful circuit simulator, the Simulation Program with Integrated Circuit Emphasis (SPICE), as a general systems simulator, any highly non-linear stiff system can be simulated. Furthermore, the theoretical findings of network thermodynamics are important new contributions. The contribution of a metric structure to thermodynamics compliments and goes beyond other recent work in this area. The application of topological reasoning through Tellegen's theorem shows that a mathematical structure exists into which all physical systems can be represented canonically. The old results in non-equilibrium thermodynamics due to Onsager can be reinterpreted and extended using these new, more holistic concepts about systems. Some examples are given. These are but a few of the many applications of network thermodynamics that have been proven to extend our capacity for handling the highly interactive, non-linear systems that populate both biology and chemistry. The presentation is carried out in the context of the recent growth of the field of complexity science. In particular, the context used for this discussion derives from the work of the mathematical biologist, Robert Rosen.     

State-variable planning under structural restrictions: algorithms and complexity

Computationally tractable planning problems reported in the literature so far have almost exclusively been defined by syntactical restrictions. To better exploit the inherent structure in problems, it is probably necessary to study also structural restrictions on the underlying state-transition graph. The exponential size of this graph, though, makes such restrictions costly to test. Hence, we propose an intermediate approach, using a state-variable model for planning and defining restrictions on the separate state-transition graphs for each state variable. We identify such restrictions which can tractably be tested and we present a planning algorithm which is correct and runs in polynomial time under these restrictions. The algorithm has been implemented and it outperforms Graphplan on a number of test instances. In addition, we present an exhaustive map of the complexity results for planning under all combinations of four previously studied syntactical restrictions and our five new structural restrictions. This complexity map considers both the optimal and non-optimal plan generation problem.     

Performance Metrics and Models for Shared Cache

Performance metrics and models are prerequisites for scientific understanding and optimization. This paper introduces a new footprint-based theory and reviews the research in the past four decades leading to the new theory. The review groups the past work into metrics and their models in particular those of the reuse distance, metrics conversion, models of shared cache, performance and optimization, and other related techniques.     

GeoEntropy: A measure of complexity and similarity

Measuring the complexity of a pattern expressed either in time or space has been introduced to quantify the information content of the pattern, which can then be applied for classification. Such information measures are particularly useful for the understanding of systems complexity in many fields of sciences, business and engineering. The novel concept of geostatistical entropy (GeoEntropy) as a measure of pattern complexity and similarity is addressed in this paper. It has been experimentally shown that GeoEntropy is an effective algorithm for studying signal predictability and has superior capability of classifying complex bio-patterns.     

WAS: A weighted attribute-based strategy for cluster test selection

In past decades, many techniques have been proposed to generate and execute test cases automatically. However, when a test oracle does not exist, execution results have to be examined manually. With increasing functionality and complexity of today's software, this process can be extremely time-consuming and mistake-prone. A CTS-based (cluster test selection) strategy provides a feasible solution to mitigate such deficiency by examining the execution results only with respect to a small number of selected test cases. It groups test cases with similar execution profiles into the same cluster and selects them from each cluster. Some well-known CTS-based strategies are one per cluster, n (a predefined value which is greater than 1) per cluster, adaptive sampling, and execution-spectra-based sampling (ESBS). The ultimate goal is to reduce testing cost by quickly identifying the executions that are likely to fail. However, improperly grouping the test cases will significantly diminish the effectiveness of these strategies (by examining results of more successful executions and fewer failed executions). To overcome this problem, we propose a weighted attribute-based strategy (WAS). Instead of clustering test cases based on the similarity of their execution profiles only once like the aforementioned CTS-based strategies, WAS will conduct more than one iteration of clustering using weighted execution profiles by also considering the suspiciousness of each program element (statement, basic block, decision, etc.), where the suspiciousness in terms of the likelihood of containing bugs can be computed by using various software fault localization techniques. Case studies using seven programs (make, ant, sed, flex, grep, gzip, and space) and four CTS-based strategies (one per cluster sampling, n per cluster sampling, adaptive sampling, and ESBS) were conducted to evaluate the effectiveness of WAS on 184 faulty versions containing either single or multiple bugs. Experimental results suggest that the proposed WAS strategy outperforms other four CTS-based strategies with respect to both recall and precision such that output verification is focused more strongly on failed executions.     

Turing machines, transition systems, and interaction

This paper presents persistent Turing machines (PTMs), a new way of interpreting Turing-machine computation, based on dynamic stream semantics. A PTM is a Turing machine that performs an infinite sequence of “normal” Turing machine computations, where each such computation starts when the PTM reads an input from its input tape and ends when the PTM produces an output on its output tape. The PTM has an additional worktape, which retains its content from one computation to the next; this is what we mean by persistence.A number of results are presented for this model, including a proof that the class of PTMs is isomorphic to a general class of effective transition systems called interactive transition systems; and a proof that PTMs without persistence (amnesic PTMs) are less expressive than PTMs. As an analogue of the Church-Turing hypothesis which relates Turing machines to algorithmic computation, it is hypothesized that PTMs capture the intuitive notion of sequential interactive computation.     

#BIS-hardness for 2-spin systems on bipartite bounded degree graphs in the tree non-uniqueness region

Counting independent sets on bipartite graphs (#BIS) is considered a canonical counting problem of intermediate approximation complexity. It is conjectured that #BIS neither has an FPRAS nor is as hard as #Sat to approximate. We study #BIS in the general framework of two-state spin systems on bipartite graphs. We define two notions, nearly-independent phase-correlated spins and unary symmetry breaking. We prove that it is #BIS-hard to approximate the partition function of any 2-spin system on bipartite graphs supporting these two notions. Consequently, we classify the complexity of approximating the partition function of antiferromagnetic 2-spin systems on bounded-degree bipartite graphs.     

Analysis of complexity indices for classification problems: Cancer gene expression data

Currently, cancer diagnosis at a molecular level has been made possible through the analysis of gene expression data. More specifically, one usually uses machine learning (ML) techniques to build, from cancer gene expression data, automatic diagnosis models (classifiers). Cancer gene expression data often present some characteristics that can have a negative impact in the generalization ability of the classifiers generated. Some of these properties are data sparsity and an unbalanced class distribution. We investigate the results of a set of indices able to extract the intrinsic complexity information from the data. Such measures can be used to analyze, among other things, which particular characteristics of cancer gene expression data mostly impact the prediction ability of support vector machine classifiers. In this context, we also show that, by applying a proper feature selection procedure to the data, one can reduce the influence of those characteristics in the error rates of the classifiers induced.     

HypEs: an architecture for hypermedia-enabled expert systems

Expert systems and hypermedia constitute two important technologies for organizations to create, store, and manage information products. The purpose of our research is to develop an architectural blueprint for the construction of hypermedia-enabled expert systems. We propose an architecture termed HypEs (Hypermedia-enabled Expert System) for the development of media-rich expert systems. The integration of hypermedia technologies and expert systems can provide significant potential benefits by enabling the storage and manipulation of non-textual knowledge, enhancing the effectiveness of both knowledge acquisition from the sources of expertise and knowledge transfer to non-expert users. An experimental analysis that contrasts the hypermedia-enabled and text-restricted expert systems provides results that underscore the usefulness of hypermedia techniques in enhancing the effectiveness of expert systems in practical applications.     

On system gains for linear and nonlinear systems

System gains, and bounds for system gains, are determined for stable linear and nonlinear systems in different signal setups which include ℓ_p signal setups and certain persistent signal generalizations of the ℓ₂ and ℓ₁ signal setups. These results show that robust H_∞ and ℓ₁ control generalize to very versatile persistent signal settings. Relationships between different system gains are also derived. Finally, an application of nonlinear system gain bounds is given by establishing induced ℓ_∞ modelling error bounds for a class of (generalized) piecewise linear systems approximated with simpler linear time-invariant models.     

Designing sustainable work systems: The need for a systems approach

There is a growing discussion concerning sustainability. While this discussion was at first mainly focused on a society level – and sometimes regarding especially environmental problems, one can now see that this topic is of increasing relevance for companies worldwide and even the social dimension of this three pillar approach is gaining more and more importance. This leads to some questions: Is sustainability already a part of human factors thinking or do we have to further develop our discipline? How can we define sustainable work systems? What are the topics we have to consider? Do we need a new systems ergonomics perspective regarding whole value creation chains and a life-cycle perspective concerning products (and work systems)? How can we deal with potential contradictions about social, ecological, and economic goals?     

Local and global dominance conditions for the weighted earliness scheduling problem with no idle time

In this paper, we present dominance conditions for the single machine weighted earliness scheduling problem with no idle time. We also propose an algorithm that can be used to improve upper bounds for the weighted earliness criterion and lower bounds for an earliness/tardiness problem. The computational tests show that the algorithm is superior to an initial heuristic schedule and an existing adjacency condition.