Industrial statistics: The challenges and the research

ABSTRACT

Industrial problems have stimulated an enormous amount of valuable statistical research, from the t-test to advanced statistical tools for quality. Industry continues to generate challenging problems for statistical design, modeling, and analysis. Useful articles are published in our journals, often stimulated by industrial applications. Nonetheless, there is concern that research in industrial statistics is falling well short of its potential for providing interesting problems, that some of the most exciting problems are not getting space in our journals, and that few statisticians working in industry are publishing research. This article endeavors to map out the current state of research in industrial statistics, to describe major issues that need to be addressed, and to discuss whether the research is on target to meet those challenges.     

Statistical transfer learning: A review and some extensions to statistical process control

ABSTRACT

The rapid development of information technology, together with advances in sensory and data acquisition techniques, has led to the increasing necessity of handling datasets from multiple domains. In recent years, transfer learning has emerged as an effective framework for tackling related tasks in target domains by transferring previously-acquired knowledge from source domains. Statistical models and methodologies are widely involved in transfer learning and play a critical role, which, however, has not been emphasized in most surveys of transfer learning. In this article, we conduct a comprehensive literature review on statistical transfer learning, i.e., transfer learning techniques with a focus on statistical models and statistical methodologies, demonstrating how statistics can be used in transfer learning. In addition, we highlight opportunities for the use of statistical transfer learning to improve statistical process control and quality control. Several potential future issues in statistical transfer learning are discussed.     

Collaboration for Innovation in Closed System Industries: The Case of the Aviation Industry

Abstract:

Unlike platform industries, closed system industries have proprietary product architectures that hinder independent components innovation; however, system integrators of closed architecture products still use collaboration extensively for innovation. While the aviation training industry has exhibited closed system architecture throughout its history, several forms of collaboration have been observed between its players in the new economy. Various forms of collaboration agreements and setups have been implemented for creating new products, entering new markets and improving operational efficiency. These cases highlight the need for collaboration in the new economy where technological complexity and the need to acquire dynamic capabilities are turning competitors into co-opetitors.     

Discussion on “Real-time monitoring of events applied to syndromic surveillance”

Abstract

I discuss the article “Real-time monitoring of events applied to syndromic surveillance” by Sparks and collaborators. This discussion focuses on how statistical network modeling and inference can be used to augment the analysis done in their paper. In particular I describe what network models can be used to characterize the dynamics and interactions of Twitter users, and more broadly how network analysis can be used to benefit statistical process monitoring. I hope to not only provide readers a new perspective on how to approach statistical process monitoring in the context of social interactions, but also to motivate future research that address the unique challenges facing quality engineers.     

Exploring the relationship between types of family involvement and collaborative innovation in design-intensive firms: insights from two leading players in the furniture industry

ABSTRACT

Innovation in family firms has attracted considerable interest from scholars and practitioners in recent years. However, further theoretical and empirical research is needed to illuminate the intricate relationship between family involvement and innovation. This article studies the effect of different types of family involvement on the management of collaborative innovation. Based on empirical evidence from two leading Italian design-intensive firms in the furniture industry (B&B Italia and Cassina), this study illuminates how family involvement in control and management influences the way design-intensive firms collaborate with external designers to innovate their products. We use two indicators, design renewal and design identity, to capture differences in collaboration approaches through which design-intensive family firms involve external designers. Thus, our findings contribute to understanding how collaborative innovation is managed in family firms. This article also provides family firm owners and managers with insights on the forces that influence the collaborative innovation processes in design-intensive firms.     

Influence of Green Practices on Organizational Competitiveness: A Study of the Electrical and Electronics Industry

Abstract

The purpose of this article is to verify the efficacy of green practices in influencing competitive enablers of organizations in the electrical and electronics industry. This study applies quantitative modeling, supported by a survey of 70 companies in southern Brazil and a structural equations model. The model includes four constructs: green strategy, green innovation, externalities management in green operations, and information management in green operations. The model also includes three factors influenced by the constructs that facilitate the construction of the organizational competitiveness: compliance, strategic drivers, and corporate image. The main result obtained suggests that green strategy and green innovation are more likely to influence competitiveness in the industry, and information management only partially influences competitiveness, while externalities management appears to have no influence.     

A control scheme for monitoring the frequency and magnitude of an event

While many control charts have been developed for monitoring the time interval (t) between the occurrences of an event, many other charts are employed to examine the magnitude (x) of the event. These two types of control charts have usually been investigated and applied separately with limited syntheses in conventional statistical process control (SPC) methods. This article presents an SPC method for simultaneously monitoring the time interval t and magnitude x. It, essentially, combines a t chart and an x chart, and is therefore referred to as a t&x chart. The new chart is more effective than an individual t chart or individual x chart for detecting the out-of-control status of the event, in particular for detecting downward shifts (sparse occurrence and/or small magnitude). More profound is that, compared with an individual t or x chart, the detection effectiveness of the t&x chart is more invariable against different types of shifts, i.e. t shift, x shift and joint shift in t and x. The t&x chart has demonstrated its potential not only for manufacturing systems, but also for non-manufacturing sectors such as supply chain management, office administration and health care industry.     

Quality and statistical thinking in a parliament and beyond

ABSTRACT

After decades of an intensive academic career, with research activities having a strong statistical and quality background, I was given the opportunity of running twice for election to the National Parliament of Portugal. This article is mostly about the challenging experience of being a Member of Parliament from 2009–2015. I aim to provide sufficient evidence to convince the reader that statistical thinking, quality tools, and fact-based approaches are necessary to better governing. These tools and approaches can help to provide a better understanding of how Parliaments work and some of the strongest features of their organizational culture. Routine application of these tools can yield better results, increased efficiency and efficacy in Parliaments, politics and in public policy making.

For that purpose, I provide specific illustrations, which show how I applied statistical tests, variation analysis, clustering, and Bayesian interpretations to several situations related with the Portuguese Parliament. The goal of this article is to provide enough support to show that: (i) statistical or quality thinking and tools can help to better understand and improve Parliaments, as well as come up with better evidence-based decisions made by politicians; and (ii) Parliaments and societies are likely to get better if more people with a sound statistical background accept the challenge of becoming Members of Parliament, at least for a while.     

Process monitoring research with various estimator-based MEWMA control charts

Multivariate exponentially weighted moving average (MEWMA) control chart with five different estimators as population covariance matrix is rarely applied to monitor small fluctuations in the statistical process control. In this article, mathematical models of the five estimators (S₁, S₂, S₃, S₄, S₅) are established, with which the relevant MEWMA control charts are obtained, respectively. Thereafter, the process monitoring performance of the five control charts is simulated. And the simulation results show that the S₄ estimator-based MEWMA control chart is of the best performance both in step offset failure mode and ramp offset failure mode. Since the inline process monitoring of photovoltaic manufacturing is intended to be a problem of multivariate statistics process analysis, the feasibility and effectiveness of the proposed model are elaborated in the case study during the cell testing and sorting process control for the fabrication of multicrystalline silicon solar cells.     

Statistical distribution of the optical intensity obtained using a Gaussian Schell model for space-to-ground link laser communications

Abstract

Based on the characteristics of the laser device and the inevitable error of the processing technique, a laser beam emitted from a communication terminal can be represented by the Gaussian Schell model (GSM). In space-to-ground link laser communications, the optical intensity is affected by the source coherence parameter and the zenith angle. With full consideration of these two parameters, the statistical distribution model of the optical intensity with a GSM laser in both downlink and uplink is derived. The simulation results indicate that increasing the source coherence parameter has an effect on the statistical distribution of the optical intensity; this effect is highly similar to the effect of a larger zenith angle. The optical intensity invariably degrades with increasing source coherence parameter or zenith angle. The results of this work can promote the improvement of the redundancy design of a laser communication receiver system.     

The effect of industry leaders’ exploratory innovation on competitor performance

ABSTRACT

This paper examines the effect of an industry leader’s exploratory innovation, defined as the innovation embodying novel knowledge relative to the firm’s extant knowledge, on the performance of its direct competitors. We argue that an industry leader’s exploratory innovation can benefit its competitors, resulting in an average increase in competitors’ sales. The benefit can come from advantageous inter-industry structure, higher perceived status through association, and expanded knowledge pool. The extent of benefit, however, is conditional on the number of competitors in the industry as well as the level of competitors' financial slack and Return on Assets (ROA). Using data on the U.S. computer sector, we find support for our hypotheses. This study suggests that while an industry leader’s exploratory innovation is intended to further its own interests, it also affects the plight of its direct competitors.     

Latent Structures-Based Multivariate Statistical Process Control: A Paradigm Shift

ABSTRACT

The basic fundamentals of statistical process control (SPC) were proposed by Walter Shewhart for data-starved production environments typical in the 1920s and 1930s. In the 21st century, the traditional scarcity of data has given way to a data-rich environment typical of highly automated and computerized modern processes. These data often exhibit high correlation, rank deficiency, low signal-to-noise ratio, multistage and multiway structures, and missing values. Conventional univariate and multivariate SPC techniques are not suitable in these environments. This article discusses the paradigm shift to which those working in the quality improvement field should pay keen attention. We advocate the use of latent structure–based multivariate statistical process control methods as efficient quality improvement tools in these massive data contexts. This is a strategic issue for industrial success in the tremendously competitive global market.     

Prescription for Transitioning Engineers into Managers

ABSTRACT

Technology's increasing importance and complexity have increased the need for managers with a scientific or engineering background. Furthermore, as the number of college-trained entrants into industry has grown, the perceived need for in-company training programs has decreased. Apparently, many feel that these programs are redundant or that the old-time “apprenticeship” approach to management is no longer relevant.

This article describes the resources and time required to transition highly skilled engineers into equally competent managers. Included is a discussion of the roles of education, in-company training, and apprenticeship programs.     

Investments for New Product Development: A Break-Even Time Analysis

Abstract

Combining the product-process matrix and cost-volume-profit analysis, we identify a pattern of annual cash flows for new product development (NPD) and name it the New Product Investment Curve (NPIC). A sample of 411 firms provides confirming evidence for the NPIC. On average, firms needed 12 years to recover their initial and subsequent investments for NPD. The break-even time, however, exhibits significant differences across industries depending on the speed of innovation and the cost structure of each industry. Engineering managers in an industry with high R&D and high fixed costs need to prepare for longer break-even times than those in other industries. This article provides implications for the value of cooperation between engineering managers and financial managers in NPD.     

Jump regression,image processing,and quality control

ABSTRACT

Images have been widely used in manufacturing applications for monitoring production processes, partly because they are often convenient and economic to acquire by different types of imaging devices. Medical imaging techniques, such as CT, PET, X-ray, ultrasound, magnetic resonance imaging (MRI), and functional MRI, have become a basic medical diagnosis tool nowadays. Satellite images are also commonly used for monitoring the changes of the earth’s surface. In all these applications, image comparison and monitoring are the common and fundamentally important statistical problems that should be addressed properly. In computer science, applied mathematics, statistics and some other disciplines, there have been many image processing methods proposed. In this article, I will discuss (i) a powerful statistical tool, called jump regression analysis (JRA), for modeling and analyzing images and other types of data with jumps and other singularities involved, (ii) some image processing problems and methods that are potentially useful for image comparison and monitoring, and (iii) some of my personal perspectives about image comparison and monitoring.     

Statistical process monitoring of time-dependent data

ABSTRACT

During the last decades, we evolved from measuring few process variables at sparse intervals to a situation in which a multitude of variables are measured at high speed. This evidently provides opportunities for extracting more information from processes and to pinpoint out-of-control situations, but transforming the large data streams into valuable information is still a challenging task. In this contribution we will focus on the analysis of time-dependent processes since this is the scenario most often encountered in practice, due to high sampling systems and the natural behavior of many real-life applications. The modeling and monitoring challenges that statistical process monitoring (SPM) techniques face in this situation will be described and possible routes will be provided. Simulation results as well as a real-life data set will be used throughout the article.     

The co-location of innovation and production in clusters

ABSTRACT

This paper quantifies the extent of co-location of innovation and production for industry clusters with varying knowledge intensity. If input-output, knowledge, and skill linkages are interdependent and geographically bounded, then we would expect innovation and production to be co-located in regional clusters. However, theory predicts that the degree of agglomeration benefits associated with co-location may vary across economic activities with different knowledge intensity. Using data from the U.S. Cluster Mapping Project, I develop measures of the co-location of innovation and production for 27 industry clusters, examining patterns across regions and over time (1998–2015) in the United States. I find that there is a significant co-location of innovation and production for many clusters, especially for those with higher knowledge intensity. This paper focuses on the Information Technology and Analytical Instruments cluster and the Automotive cluster to illustrate the co-location measures and the micro-geography of innovation and production.     

A Synthetic Control Chart for Monitoring the Ratio of Two Normal Variables

Very recently, monitoring the ratio of two normal random variables by means of control charts has been investigated in statistical process control literature. The industrial implementation of these control charts involves monitoring of processes where the correct proportion of two ingredients or elements within a product should be maintained under statistical control, monitoring of quality characteristics measuring the performance of a product as the ratio before and after some specific operation, for example, a chemical reaction following the introduction of an additive in a product, and monitoring of a chemical or physical property of a product, which is itself defined and computed as a ratio. This paper presents a Phase II synthetic control chart with each subgroup consisting of n > 1 sample units. Several tables are generated and commented to show the statistical performance of the investigated chart for known and random shift sizes affecting the in‐control ratio. A performance comparison with another control chart already proposed in literature shows the advantages associated to the implementation of the synthetic control chart. An illustrative example from the food industry is given for illustration. Copyright © 2015 John Wiley & Sons, Ltd.     

What facilitates external knowledge utilisation in SMEs? – An optimal configuration between openness intensity and organisational moderators

ABSTRACT

This study explores the complex relationships between open innovation (OI) climate and OI activities by investigating the changing moderating effects of organisational facilitators in small innovative firms. Our partial least squares structural equation modelling analysis suggests (1) OI-friendly climate promotes OI activities, (2) this process is further facilitated by various organisational efforts, but (3) the efforts firms must put in are proportional to the level of openness intensity. The findings also suggest that systematic knowledge management is the most basic facilitator, while entrepreneurial orientation is generally underperformed despite its high importance. This study provides implications for managers and policymakers who lead OI adoption and implementation.

Abbreviation: SMEs - Small and Medium-sized Enterprises; PLS-SEM - Partial Least Squares - Structural Equation Modeling     

Developing a TRL-oriented roadmap for the adoption of biocomposite materials in the construction industry

The construction industry is a major contributor to environmental pollution. The effect of the construction industry on the environment may be mitigated using eco-friendly construction materials, such as biocomposites. Once developed, biocomposites may offer a viable alternative to the current materials in use. However, biocomposites are lagging in terms of adoption and eventual use in the construction industry. This article provides insights into the steps for biocomposites to become a product that is ready to use by the construction industry in a structural role. The development and the adoption of such a material is tackled with the use of two concepts, i.e., technology readiness level and roadmapping, and explored in a case study on the “liquid wood”. Furthermore, interviews in the construction industry are carried out to identify the industry’s take on biocomposites. A customized roadmap, which underlines a mostly nontechnical perspective concerning this material, has emerged. Additionally, the adoption and diffusion issues that the “liquid wood” may encounter are outlined and complemented with further recommendations.