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This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

This chapter focuses on the international aspects of auditing in the context of the airline industry for the year 2018. This chapter finds that International Standards on Auditing have been widely adopted in the global context. This chapter also analyses several observations related to the composition of audit firms (Big 4 vs. non-Big 4), types of audit opinions, emphasis of matter, other matters, material uncertainty related to going-concern, and types of auditors (single or joint auditor). This chapter covers the frequency of the four elements of describing key audit matters (KAM) in the audit reports in the global and auditor context as well as the KAMs observed in the airline industry and classifies them as industry-specific KAMs and entity-specific KAMs. In addition, this chapter analyses the requirements of the expanded audit report of the UK which includes the declaration of materiality threshold and scope of the audit in connection with the materiality and KAMs considering UK and non-UK airlines.

Most setup management techniques associated with electronic assembly operations focus on component similarity in grouping boards for batch processing. These process planning techniques often minimize setup times. On the contrary, grouping with respect to component geometry and frequency has been proved to further minimize assembly time. Thus, we propose the Placement Location Metric (PLM) algorithm to recognize and measure the similarity between printed circuit board (PCB) patterns. Grouping PCBs based on the geometric and frequency patterns of components in boards will form clusters of locations and, if these clusters are common between boards, similarity among layouts can be recognized. Hence, placement time will decrease if boards are grouped together with respect to the geometric similarity because the machine head will travel less. Given these notions, this study develops a new technique to group PCBs based on the essences of both component commonality and the PLM. The proposed pattern recognition method in conjunction with the Improved Group Setup (IGS) technique can be viewed as an extended enhancement to the existing Group Setup (GS) technique, which groups PCBs solely according to component similarity. Our analysis indicates that the IGS performs relatively well with respect to an array of existing setup management strategies. Experimental results also show that the IGS produces a better makespan than its counterparts over a low range of machine changeover times. These results are especially important to operations that need to manufacture quickly batches of relatively standardized products in moderate to larger volumes or in flexible cell environments. Moreover, the study provides justification to adopt different group management paradigms by electronic suppliers under a variety of processing conditions.

Each of the four objectives can be applied within the military training environment. Military training often requires that soldiers achieve specific levels of performance or proficiency in each phase of training. For example, training courses impose entrance and graduation criteria, and awards are given for excellence in military performance. Frequently, training devices, training media, and training evaluators or observers also directly support the need to diagnose performance strengths and weaknesses. Training measures may be used as indices of performance, and to indicate the need for additional or remedial training.

This chapter deals with the patterns of International Financial Reporting Standards’ accounting policy choices that have been analyzed by several authors in a country-specific context. Instead of a country-specific context, this chapter adopts a sector-specific approach in terms of the airline industry in a regional and global context in order to observe the patterns of cosmetic and non-cosmetic policy options. Cosmetic policy options are related to the presentation of financial information which is not expected to impact the comparability of financial information versus non-cosmetic policy options are considered to be policy options that are related to measurement and, therefore, if there is more than one allowable accounting treatment, the comparability of financial information weakens. In the context of the airline industry, this chapter considers the patterns of policy choices related to IAS 1 Presentation of Financial Statements, IAS 2 Inventory, IAS 7 Statement of Cash Flows, IAS 16 Property, Plant and Equipment, IAS 38 Intangible Assets, and IAS 40 Investment Property, within the framework of frequently observed policy options as well as taking depreciation methods and expected useful life into consideration in terms of industry-specific policy options in order to observe whether there is uniformity rather than diversity in the airline industry for presentation and measurement.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.