Emory W. Zimmers's research while affiliated with Lehigh University and other places

... Earlier work with the Greenfield Coalition had demonstrated the value of attention to these processes. 4,5,6,7 Another important component of module development from the Greenfield Coalition design process was placing the module within a learning context. This context requires defining the motivation, the objectives, and the prior knowledge of the participants. ...

... Examples of the complexity of the control strategy for this kind of solutions are reported in [5] for rolling approach, in [6] for sliding approach and [7] for gaiting approach. The choice of using a parallel gripper is justified in the manufacturing field by Bracken [8], who proposed a geometrical classification of parts to be gripped into six shape categories (i.e., spherical, rectangular, cylindrical, triangular, holed and flexible) and stated that the gripper able to deal with most shapes is the parallel two-jaw gripper. ...

... This complexity of lean has produced awareness in manufacturers and researchers of the whole world to apply such tools that are beneficial for lean in the system (Swank, 2003), to acquire the best results like improve lead times, customers demand and controlling cost and quality (Goldsby, Griffis, & Roath, 2006;Rafique, Ab Rahman, Saibani, Arsad, & Saadat, 2016). In order to do so, the lean tool of value stream mapping is beneficial since it categorizes the process to value added and non-value added times, laying groundwork for improvements (Christian & Zimmers, 1999). Lean can be considered as a philosophy which helps to make the system effective and efficient for industries. ...

... Gupta (1993) proposed a similarity coefficient which incorporates several production factors such as operation sequences, production volumes, alternative process routings. Lee and Garcia-Diaz (1996) Hamming (D) Use a 3-phase network-flow approach Leem and Chen (1996) Jaccard Fuzzy set theory Lin et al. (1996) Bray-Curtis (D) Heuristic; workload balance within cells Sarker (1996) Many Review of similarity coefficient Al-sultan and Fedjki (1997) Hamming (D) Genetic algorithm Askin et al. (1997) MaxSC Consider flexibility of routing and demand Baker and Maropoulos (1997) Jaccard, Baker and Maropoulos (1997) Black box clustering algorithm Cedeno and Suer (1997) -Approach to ''remainder clusters'' Masnata and Settineri (1997) Euclidean (D) Fuzzy clustering theory Mosier et al. (1997) Many Review of similarity coefficients Offodile and Grznar (1997) Offodile (1991) Parts coding and classification analysis Wang and Roze (1997) Jaccard, Kusiak (1987), CS Modify p-median model Cheng et al. (1998) Manhattan (D) TSP by genetic algorithm Jeon et al. (1998a) Jeon et al. (1998b p-median Onwubolu and Mlilo (1998) Jaccard A new algorithm (SCDM) Srinivasan and Zimmers (1998) Manhattan (D) Fractional cell formation problem Wang (1998) -A linear assignment model Ben-Arieh and Sreenivasan (1999) Euclidean (D) A distributed dynamic algorithm Lozano et al. (1999) Jaccard Tabu search Sarker and Islam (1999) Many Performance study Baykasoglu and Gindy (2000) Jaccard Tabu search Chang and Lee (2000) Kusiak (1987) Multi-solution heuristic Josien and Liao (2000) Euclidean (D) Fuzzy set theory Lee-post (2000) Offodile (1991) Use a simple genetic algorithm Won (2000a) Won and Kim(1997) Alternative process plan with p-median model Won (2000b) Jaccard, Kusiak (1987) Two-phase p-median model Dimopoulos and Mort (2001) Jaccard Genetic algorithm Samatova et al. (2001) Five dissimilarity coefficients Vector perturbation approach a No specific SC mentioned. Akturk and Balkose (1996) revised the Levenshtein distance measure to penalize the backtracking parts neither does award the commonality. ...

... Previously, it was challenging to manufacture the complex organic shapes derived by topology optimization due to technical limitations or the need for considerable resources to materialize the designs. However, these manufacturing challenges have been overcome by technological developments such as advanced computer numerical control (CNC) (Newman and Nassehi 2007), computer-aided design (CAD) (Groover and Zimmers 1983;Ji and Marefat 1997), 3-D printing, and additive manufacturing (Wong and Hernandez 2012;Frazier 2014;Yan et al. 2018;Shahrubudin et al. 2019). ...

... It has been subsequently applied in the manufacturing scheduling context as it is stated to be an appropriate objective for just-in-time production systems, or any other situation where a uniform treatment of the jobs is desirable (see, e.g., in [21][22][23][24]). In the flow shop/job shop scheduling context, it has been employed by [25][26][27][28][29][30][31][32]. ...

... Moreover as Bozkir and Akcapinar Sezer point out, approaches which forecast the demand for a served menu can present many benefits to institutions as it would optimize the balance of supply and demand in name of saving resources and work power [1]. At this point, Sundararajan et al. address the importance of information technology and services, computer aided tools providing intelligence to make real time decisions [3]. With this motivation, Sundararajan et al. implemented a decision support system for making operational decisions in food processing industry which is based on optimization techniques and focuses on determining optimum production scenario for every week based on the tradeoffs between service levels, inventories, costs and capacity [3]. ...

... Wireless communication between the tag and reader is influenced by factors such as the type of reader, the position of the tag, the direction of the tag, the material of the object to which the tag is attached, the angle of the antenna, and the speed of the object. [6] When other radio frequencies interfere with the frequency with which the tag and reader communicate, the reader cannot identify the tag successfully. For the reasons stated above it is very clear that the object attached to the tag or material contained in the surrounding area can result in changes in tag performance and reader. ...